Mercurial > octave-nkf
changeset 9064:7c02ec148a3c
Check grammar on all .cc files
Same check as previously done on .m files
Attempt to enforce some conformity in documentation text for rules
such as two spaces after a period, commas around latin abbreviations, etc.
line wrap: on
line diff
--- a/doc/interpreter/arith.txi Mon Mar 30 19:48:56 2009 -0400 +++ b/doc/interpreter/arith.txi Sat Mar 28 13:57:22 2009 -0700 @@ -21,7 +21,7 @@ @chapter Arithmetic Unless otherwise noted, all of the functions described in this chapter -will work for real and complex scalar or matrix arguments. Functions described as @dfn{mapping functions} apply the given operation to each element when given a matrix argument. +will work for real and complex scalar or matrix arguments. Functions described as @dfn{mapping functions} apply the given operation to each element when given a matrix argument. @menu * Utility Functions:: @@ -152,7 +152,7 @@ @ifinfo @code{pi/180} @end ifinfo - (e.g. @code{sin (30 * pi/180)} returns the sine of 30 degrees). + (e.g., @code{sin (30 * pi/180)} returns the sine of 30 degrees). @DOCSTRING(sin) @DOCSTRING(cos)
--- a/src/DLD-FUNCTIONS/__magick_read__.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/__magick_read__.cc Sat Mar 28 13:57:22 2009 -0700 @@ -349,7 +349,7 @@ @deftypefn {Function File} {@var{m} =} __magick_read__(@var{fname}, @var{index})\n\ @deftypefnx{Function File} {[@var{m}, @var{colormap}] =} __magick_read__(@var{fname}, @var{index})\n\ @deftypefnx{Function File} {[@var{m}, @var{colormap}, @var{alpha}] =} __magick_read__(@var{fname}, @var{index})\n\ -Read images with ImageMagick++. In general you should not be using this function.\n\ +Read images with ImageMagick++. In general you should not be using this function.\n\ Instead you should use @code{imread}.\n\ @seealso{imread}\n\ @end deftypefn") @@ -752,7 +752,7 @@ "-*- texinfo -*-\n\ @deftypefn {Function File} {} __magick_write__(@var{fname}, @var{fmt}, @var{img})\n\ @deftypefnx {Function File} {} __magick_write__(@var{fname}, @var{fmt}, @var{img}, @var{map})\n\ -Write images with ImageMagick++. In general you should not be using this function.\n\ +Write images with ImageMagick++. In general you should not be using this function.\n\ Instead you should use @code{imwrite}.\n\ @seealso{imread}\n\ @end deftypefn") @@ -880,7 +880,7 @@ DEFUN_DLD (__magick_finfo__, args, , "-*- texinfo -*-\n\ @deftypefn {Loadable File} {} __magick_finfo__(@var{fname})\n\ -Read image information with GraphicsMagick++. In general you should\n\ +Read image information with GraphicsMagick++. In general you should\n\ not be using this function. Instead you should use @code{imfinfo}.\n\ @seealso{imfinfo, imread}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/amd.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/amd.cc Sat Mar 28 13:57:22 2009 -0700 @@ -55,26 +55,26 @@ @deftypefn {Loadable Function} {@var{p} =} amd (@var{s})\n\ @deftypefnx {Loadable Function} {@var{p} =} amd (@var{s}, @var{opts})\n\ \n\ -Returns the approximate minimum degree permutation of a matrix. This\n\ +Returns the approximate minimum degree permutation of a matrix. This\n\ permutation such that the Cholesky factorization of @code{@var{s} (@var{p},\n\ @var{p})} tends to be sparser than the Cholesky factorization of @var{s}\n\ -itself. @code{amd} is typically faster than @code{symamd} but serves a\n\ +itself. @code{amd} is typically faster than @code{symamd} but serves a\n\ similar purpose.\n\ \n\ The optional parameter @var{opts} is a structure that controls the\n\ -behavior of @code{amd}. The fields of these structure are\n\ +behavior of @code{amd}. The fields of these structure are\n\ \n\ @table @asis\n\ @item opts.dense\n\ Determines what @code{amd} considers to be a dense row or column of the\n\ -input matrix. Rows or columns with more that @code{max(16, (dense *\n\ +input matrix. Rows or columns with more that @code{max(16, (dense *\n\ sqrt (@var{n})} entries, where @var{n} is the order of the matrix @var{s},\n\ are igorned by @code{amd} during the calculation of the permutation\n\ The value of dense must be a positive scalar and its default value is 10.0\n\ \n\ @item opts.aggressive\n\ If this value is a non zero scalar, then @code{amd} performs agressive\n\ -absorption. The default is not to perform agressive absorption.\n\ +absorption. The default is not to perform agressive absorption.\n\ @end table\n\ \n\ The author of the code itself is Timothy A. Davis (davis@@cise.ufl.edu),\n\
--- a/src/DLD-FUNCTIONS/balance.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/balance.cc Sat Mar 28 13:57:22 2009 -0700 @@ -62,9 +62,9 @@ eigenvalue calculation are typically improved by balancing first.\n\ \n\ If two output values are requested, @code{balance} returns \n\ -the diagonal @code{d} and the permutation @code{p} separately as vectors. \n\ +the diagonal @code{d} and the permutation @code{p} separately as vectors. \n\ In this case, @code{dd = eye(n)(p,:) * diag (d)}, where @code{n} is the matrix \n\ -size. \n\ +size. \n\ \n\ If four output values are requested, compute @code{aa = cc*a*dd} and\n\ @code{bb = cc*b*dd)}, in which @code{aa} and @code{bb} have non-zero\n\
--- a/src/DLD-FUNCTIONS/besselj.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/besselj.cc Sat Mar 28 13:57:22 2009 -0700 @@ -388,10 +388,10 @@ \n\ @table @code\n\ @item besselj\n\ -Bessel functions of the first kind. If the argument @var{opt} is supplied, \n\ +Bessel functions of the first kind. If the argument @var{opt} is supplied, \n\ the result is multiplied by @code{exp(-abs(imag(x)))}.\n\ @item bessely\n\ -Bessel functions of the second kind. If the argument @var{opt} is supplied,\n\ +Bessel functions of the second kind. If the argument @var{opt} is supplied,\n\ the result is multiplied by @code{exp(-abs(imag(x)))}.\n\ @item besseli\n\ Modified Bessel functions of the first kind. If the argument @var{opt} is supplied,\n\ @@ -401,7 +401,7 @@ the result is multiplied by @code{exp(x)}.\n\ @item besselh\n\ Compute Hankel functions of the first (@var{k} = 1) or second (@var{k}\n\ -= 2) kind. If the argument @var{opt} is supplied, the result is multiplied by\n\ += 2) kind. If the argument @var{opt} is supplied, the result is multiplied by\n\ @code{exp (-I*@var{x})} for @var{k} = 1 or @code{exp (I*@var{x})} for\n\ @var{k} = 2.\n\ @end table\n\ @@ -518,12 +518,14 @@ derivatives.\n\ \n\ @example\n\ +@group\n\ K Function Scale factor (if 'opt' is supplied)\n\ --- -------- ---------------------------------------\n\ 0 Ai (Z) exp ((2/3) * Z * sqrt (Z))\n\ 1 dAi(Z)/dZ exp ((2/3) * Z * sqrt (Z))\n\ 2 Bi (Z) exp (-abs (real ((2/3) * Z *sqrt (Z))))\n\ 3 dBi(Z)/dZ exp (-abs (real ((2/3) * Z *sqrt (Z))))\n\ +@end group\n\ @end example\n\ \n\ The function call @code{airy (@var{z})} is equivalent to\n\
--- a/src/DLD-FUNCTIONS/ccolamd.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/ccolamd.cc Sat Mar 28 13:57:22 2009 -0700 @@ -58,12 +58,12 @@ @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{s}, @var{knobs}, @var{cmember})\n\ @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\ \n\ -Constrained column approximate minimum degree permutation. @code{@var{p} =\n\ +Constrained column approximate minimum degree permutation. @code{@var{p} =\n\ ccolamd (@var{s})} returns the column approximate minimum degree permutation\n\ -vector for the sparse matrix @var{s}. For a non-symmetric matrix @var{s},\n\ +vector for the sparse matrix @var{s}. For a non-symmetric matrix @var{s},\n\ @code{@var{s} (:, @var{p})} tends to have sparser LU factors than @var{s}.\n\ @code{chol (@var{s} (:, @var{p})' * @var{s} (:, @var{p}))} also tends to be\n\ -sparser than @code{chol (@var{s}' * @var{s})}. @code{@var{p} = ccolamd\n\ +sparser than @code{chol (@var{s}' * @var{s})}. @code{@var{p} = ccolamd\n\ (@var{s}, 1)} optimizes the ordering for @code{lu (@var{s} (:, @var{p}))}.\n\ The ordering is followed by a column elimination tree post-ordering.\n\ \n\ @@ -73,9 +73,9 @@ \n\ @table @code\n\ @item @var{knobs}(1)\n\ -if nonzero, the ordering is optimized for @code{lu (S (:, p))}. It will be a\n\ +if nonzero, the ordering is optimized for @code{lu (S (:, p))}. It will be a\n\ poor ordering for @code{chol (@var{s} (:, @var{p})' * @var{s} (:,\n\ -@var{p}))}. This is the most important knob for ccolamd.\n\ +@var{p}))}. This is the most important knob for ccolamd.\n\ \n\ @item @var{knob}(2)\n\ if @var{s} is m-by-n, rows with more than @code{max (16, @var{knobs} (2) *\n\ @@ -103,7 +103,7 @@ @var{n})} returns @code{1 : @var{n}}\n\ \n\ @code{@var{p} = ccolamd (@var{s})} is about the same as @code{@var{p} =\n\ -colamd (@var{s})}. @var{knobs} and its default values differ. @code{colamd}\n\ +colamd (@var{s})}. @var{knobs} and its default values differ. @code{colamd}\n\ always does aggressive absorption, and it finds an ordering suitable for\n\ both @code{lu (@var{s} (:, @var{p}))} and @code{chol (@var{S} (:, @var{p})'\n\ * @var{s} (:, @var{p}))}; it cannot optimize its ordering for\n\ @@ -111,8 +111,8 @@ @code{ccolamd (@var{s}, 1)} can.\n\ \n\ @var{stats} is an optional 20-element output vector that provides data\n\ -about the ordering and the validity of the input matrix @var{s}. Ordering\n\ -statistics are in @code{@var{stats} (1 : 3)}. @code{@var{stats} (1)} and\n\ +about the ordering and the validity of the input matrix @var{s}. Ordering\n\ +statistics are in @code{@var{stats} (1 : 3)}. @code{@var{stats} (1)} and\n\ @code{@var{stats} (2)} are the number of dense or empty rows and columns\n\ ignored by CCOLAMD and @code{@var{stats} (3)} is the number of garbage\n\ collections performed on the internal data structure used by CCOLAMD\n\ @@ -120,17 +120,17 @@ integers).\n\ \n\ @code{@var{stats} (4 : 7)} provide information if CCOLAMD was able to\n\ -continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ -invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ +continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ +invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ unsorted or contains duplicate entries, or zero if no such column exists.\n\ @code{@var{stats} (6)} is the last seen duplicate or out-of-order row\n\ index in the column index given by @code{@var{stats} (5)}, or zero if no\n\ -such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ -or out-of-order row indices. @code{@var{stats} (8 : 20)} is always zero in\n\ +such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ +or out-of-order row indices. @code{@var{stats} (8 : 20)} is always zero in\n\ the current version of CCOLAMD (reserved for future use).\n\ \n\ The authors of the code itself are S. Larimore, T. Davis (Uni of Florida)\n\ -and S. Rajamanickam in collaboration with J. Bilbert and E. Ng. Supported\n\ +and S. Rajamanickam in collaboration with J. Bilbert and E. Ng. Supported\n\ by the National Science Foundation (DMS-9504974, DMS-9803599, CCR-0203270),\n\ and a grant from Sandia National Lab. See\n\ @url{http://www.cise.ufl.edu/research/sparse} for ccolamd, csymamd, amd,\n\ @@ -340,10 +340,10 @@ \n\ For a symmetric positive definite matrix @var{s}, returns the permutation\n\ vector @var{p} such that @code{@var{s}(@var{p},@var{p})} tends to have a\n\ -sparser Cholesky factor than @var{s}. Sometimes @code{csymamd} works well\n\ -for symmetric indefinite matrices too. The matrix @var{s} is assumed to\n\ +sparser Cholesky factor than @var{s}. Sometimes @code{csymamd} works well\n\ +for symmetric indefinite matrices too. The matrix @var{s} is assumed to\n\ be symmetric; only the strictly lower triangular part is referenced.\n\ -@var{s} must be square. The ordering is followed by an elimination tree\n\ +@var{s} must be square. The ordering is followed by an elimination tree\n\ post-ordering.\n\ \n\ @var{knobs} is an optional one- to three-element input vector, with a\n\ @@ -365,27 +365,27 @@ @end table\n\ \n\ @var{cmember} is an optional vector of length n. It defines the constraints\n\ -on the ordering. If @code{@var{cmember}(j) = @var{s}}, then row/column j is\n\ -in constraint set @var{c} (@var{c} must be in the range 1 to n). In the\n\ +on the ordering. If @code{@var{cmember}(j) = @var{s}}, then row/column j is\n\ +in constraint set @var{c} (@var{c} must be in the range 1 to n). In the\n\ output permutation @var{p}, rows/columns in set 1 appear first, followed\n\ -by all rows/columns in set 2, and so on. @code{@var{cmember} = ones(1,n)}\n\ -if not present or empty. @code{csymamd(@var{s},[],1:n)} returns @code{1:n}.\n\ +by all rows/columns in set 2, and so on. @code{@var{cmember} = ones(1,n)}\n\ +if not present or empty. @code{csymamd(@var{s},[],1:n)} returns @code{1:n}.\n\ \n\ @code{@var{p} = csymamd(@var{s})} is about the same as @code{@var{p} =\n\ -symamd(@var{s})}. @var{knobs} and its default values differ.\n\ +symamd(@var{s})}. @var{knobs} and its default values differ.\n\ \n\ @code{@var{stats} (4:7)} provide information if CCOLAMD was able to\n\ -continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ -invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ +continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ +invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ unsorted or contains duplicate entries, or zero if no such column exists.\n\ @code{@var{stats} (6)} is the last seen duplicate or out-of-order row\n\ index in the column index given by @code{@var{stats} (5)}, or zero if no\n\ -such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ -or out-of-order row indices. @code{@var{stats} (8:20)} is always zero in\n\ +such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ +or out-of-order row indices. @code{@var{stats} (8:20)} is always zero in\n\ the current version of CCOLAMD (reserved for future use).\n\ \n\ The authors of the code itself are S. Larimore, T. Davis (Uni of Florida)\n\ -and S. Rajamanickam in collaboration with J. Bilbert and E. Ng. Supported\n\ +and S. Rajamanickam in collaboration with J. Bilbert and E. Ng. Supported\n\ by the National Science Foundation (DMS-9504974, DMS-9803599, CCR-0203270),\n\ and a grant from Sandia National Lab. See\n\ @url{http://www.cise.ufl.edu/research/sparse} for ccolamd, csymamd, amd,\n\
--- a/src/DLD-FUNCTIONS/cellfun.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/cellfun.cc Sat Mar 28 13:57:22 2009 -0700 @@ -1253,11 +1253,13 @@ In other words, it is equivalent to the following code:\n\ \n\ @example\n\ +@group\n\ n = length (lb);\n\ sl = cell (1, n);\n\ for i = 1:length (lb)\n\ sl@{i@} = x(lb(i):ub(i));\n\ endfor\n\ +@end group\n\ @end example\n\ \n\ If @var{X} is a matrix or array, indexing is done along the last dimension.\n\
--- a/src/DLD-FUNCTIONS/chol.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/chol.cc Sat Mar 28 13:57:22 2009 -0700 @@ -68,13 +68,13 @@ @end ifnottex\n\ \n\ Called with one output argument @code{chol} fails if @var{a} or @var{s} is\n\ -not positive definite. With two or more output arguments @var{p} flags\n\ -whether the matrix was positive definite and @code{chol} does not fail. A\n\ +not positive definite. With two or more output arguments @var{p} flags\n\ +whether the matrix was positive definite and @code{chol} does not fail. A\n\ zero value indicated that the matrix was positive definite and the @var{r}\n\ gives the factorization, annd @var{p} will have a positive value otherwise.\n\ \n\ If called with 3 outputs then a sparsity preserving row/column permutation\n\ -is applied to @var{a} prior to the factorization. That is @var{r}\n\ +is applied to @var{a} prior to the factorization. That is @var{r}\n\ is the factorization of @code{@var{a}(@var{q},@var{q})} such that\n\ @iftex\n\ @tex\n\ @@ -804,7 +804,7 @@ positive definite matrix @w{@var{A} = @var{R}'*@var{R}}, @var{R}@tie{}upper triangular,\n\ return the Cholesky@tie{}factorization of\n\ @var{A1}, where @w{A1(p,p) = A}, @w{A1(:,j) = A1(j,:)' = u} and\n\ -@w{p = [1:j-1,j+1:n+1]}. @w{u(j)} should be positive.\n\ +@w{p = [1:j-1,j+1:n+1]}. @w{u(j)} should be positive.\n\ On return, @var{info} is set to\n\ @itemize\n\ @item 0 if the insertion was successful,\n\ @@ -1122,7 +1122,7 @@ @w{@var{A}(p,p)}, where @w{p} is the permutation @*\n\ @code{p = [1:i-1, shift(i:j, 1), j+1:n]} if @w{@var{i} < @var{j}} @*\n\ or @*\n\ -@code{p = [1:j-1, shift(j:i,-1), i+1:n]} if @w{@var{j} < @var{i}}. @*\n\ +@code{p = [1:j-1, shift(j:i,-1), i+1:n]} if @w{@var{j} < @var{i}}. @*\n\ \n\ @seealso{chol, cholinsert, choldelete}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/colamd.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/colamd.cc Sat Mar 28 13:57:22 2009 -0700 @@ -215,9 +215,9 @@ @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} colamd (@var{s})\n\ @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} colamd (@var{s}, @var{knobs})\n\ \n\ -Column approximate minimum degree permutation. @code{@var{p} = colamd\n\ +Column approximate minimum degree permutation. @code{@var{p} = colamd\n\ (@var{s})} returns the column approximate minimum degree permutation\n\ -vector for the sparse matrix @var{s}. For a non-symmetric matrix @var{s},\n\ +vector for the sparse matrix @var{s}. For a non-symmetric matrix @var{s},\n\ @code{@var{s} (:,@var{p})} tends to have sparser LU factors than @var{s}.\n\ The Cholesky factorization of @code{@var{s} (:,@var{p})' * @var{s}\n\ (:,@var{p})} also tends to be sparser than that of @code{@var{s}' *\n\ @@ -225,17 +225,17 @@ \n\ @var{knobs} is an optional one- to three-element input vector. If @var{s} is\n\ m-by-n, then rows with more than @code{max(16,@var{knobs}(1)*sqrt(n))} entries\n\ -are ignored. Columns with more than @code{max(16,knobs(2)*sqrt(min(m,n)))}\n\ +are ignored. Columns with more than @code{max(16,knobs(2)*sqrt(min(m,n)))}\n\ entries are removed prior to ordering, and ordered last in the output\n\ -permutation @var{p}. Only completely dense rows or columns are removed\n\ +permutation @var{p}. Only completely dense rows or columns are removed\n\ if @code{@var{knobs} (1)} and @code{@var{knobs} (2)} are < 0, respectively.\n\ If @code{@var{knobs} (3)} is nonzero, @var{stats} and @var{knobs} are\n\ printed. The default is @code{@var{knobs} = [10 10 0]}. Note that\n\ @var{knobs} differs from earlier versions of colamd\n\ \n\ @var{stats} is an optional 20-element output vector that provides data\n\ -about the ordering and the validity of the input matrix @var{s}. Ordering\n\ -statistics are in @code{@var{stats} (1:3)}. @code{@var{stats} (1)} and\n\ +about the ordering and the validity of the input matrix @var{s}. Ordering\n\ +statistics are in @code{@var{stats} (1:3)}. @code{@var{stats} (1)} and\n\ @code{@var{stats} (2)} are the number of dense or empty rows and columns\n\ ignored by COLAMD and @code{@var{stats} (3)} is the number of garbage\n\ collections performed on the internal data structure used by COLAMD\n\ @@ -250,20 +250,20 @@ more times in the same column) or if the row indices in a column are out\n\ of order, then COLAMD can correct these errors by ignoring the duplicate\n\ entries and sorting each column of its internal copy of the matrix\n\ -@var{s} (the input matrix @var{s} is not repaired, however). If a matrix\n\ +@var{s} (the input matrix @var{s} is not repaired, however). If a matrix\n\ is invalid in other ways then COLAMD cannot continue, an error message is\n\ printed, and no output arguments (@var{p} or @var{stats}) are returned.\n\ COLAMD is thus a simple way to check a sparse matrix to see if it's\n\ valid.\n\ \n\ @code{@var{stats} (4:7)} provide information if COLAMD was able to\n\ -continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ -invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ +continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 if\n\ +invalid. @code{@var{stats} (5)} is the rightmost column index that is\n\ unsorted or contains duplicate entries, or zero if no such column exists.\n\ @code{@var{stats} (6)} is the last seen duplicate or out-of-order row\n\ index in the column index given by @code{@var{stats} (5)}, or zero if no\n\ -such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ -or out-of-order row indices. @code{@var{stats} (8:20)} is always zero in\n\ +such row index exists. @code{@var{stats} (7)} is the number of duplicate\n\ +or out-of-order row indices. @code{@var{stats} (8:20)} is always zero in\n\ the current version of COLAMD (reserved for future use).\n\ \n\ The ordering is followed by a column elimination tree post-ordering.\n\ @@ -271,7 +271,7 @@ The authors of the code itself are Stefan I. Larimore and Timothy A.\n\ Davis (davis@@cise.ufl.edu), University of Florida. The algorithm was\n\ developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\ -Ng, Oak Ridge National Laboratory. (see\n\ +Ng, Oak Ridge National Laboratory. (see\n\ @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\ @seealso{colperm, symamd}\n\ @end deftypefn") @@ -456,22 +456,22 @@ \n\ For a symmetric positive definite matrix @var{s}, returns the permutation\n\ vector p such that @code{@var{s} (@var{p}, @var{p})} tends to have a\n\ -sparser Cholesky factor than @var{s}. Sometimes SYMAMD works well for\n\ -symmetric indefinite matrices too. The matrix @var{s} is assumed to be\n\ -symmetric; only the strictly lower triangular part is referenced. @var{s}\n\ +sparser Cholesky factor than @var{s}. Sometimes SYMAMD works well for\n\ +symmetric indefinite matrices too. The matrix @var{s} is assumed to be\n\ +symmetric; only the strictly lower triangular part is referenced. @var{s}\n\ must be square.\n\ \n\ @var{knobs} is an optional one- to two-element input vector. If @var{s} is\n\ n-by-n, then rows and columns with more than\n\ @code{max(16,@var{knobs}(1)*sqrt(n))} entries are removed prior to ordering,\n\ -and ordered last in the output permutation @var{p}. No rows/columns are\n\ +and ordered last in the output permutation @var{p}. No rows/columns are\n\ removed if @code{@var{knobs}(1) < 0}. If @code{@var{knobs} (2)} is nonzero,\n\ @code{stats} and @var{knobs} are printed. The default is @code{@var{knobs} \n\ = [10 0]}. Note that @var{knobs} differs from earlier versions of symamd.\n\ \n\ @var{stats} is an optional 20-element output vector that provides data\n\ -about the ordering and the validity of the input matrix @var{s}. Ordering\n\ -statistics are in @code{@var{stats} (1:3)}. @code{@var{stats} (1) =\n\ +about the ordering and the validity of the input matrix @var{s}. Ordering\n\ +statistics are in @code{@var{stats} (1:3)}. @code{@var{stats} (1) =\n\ @var{stats} (2)} is the number of dense or empty rows and columns\n\ ignored by SYMAMD and @code{@var{stats} (3)} is the number of garbage\n\ collections performed on the internal data structure used by SYMAMD\n\ @@ -492,13 +492,13 @@ thus a simple way to check a sparse matrix to see if it's valid.\n\ \n\ @code{@var{stats} (4:7)} provide information if SYMAMD was able to\n\ -continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1\n\ -if invalid. @code{@var{stats} (5)} is the rightmost column index that\n\ +continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1\n\ +if invalid. @code{@var{stats} (5)} is the rightmost column index that\n\ is unsorted or contains duplicate entries, or zero if no such column\n\ -exists. @code{@var{stats} (6)} is the last seen duplicate or out-of-order\n\ +exists. @code{@var{stats} (6)} is the last seen duplicate or out-of-order\n\ row index in the column index given by @code{@var{stats} (5)}, or zero\n\ -if no such row index exists. @code{@var{stats} (7)} is the number of\n\ -duplicate or out-of-order row indices. @code{@var{stats} (8:20)} is\n\ +if no such row index exists. @code{@var{stats} (7)} is the number of\n\ +duplicate or out-of-order row indices. @code{@var{stats} (8:20)} is\n\ always zero in the current version of SYMAMD (reserved for future use).\n\ \n\ The ordering is followed by a column elimination tree post-ordering.\n\ @@ -507,7 +507,7 @@ The authors of the code itself are Stefan I. Larimore and Timothy A.\n\ Davis (davis@@cise.ufl.edu), University of Florida. The algorithm was\n\ developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\ -Ng, Oak Ridge National Laboratory. (see\n\ +Ng, Oak Ridge National Laboratory. (see\n\ @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\ @seealso{colperm, colamd}\n\ @end deftypefn") @@ -650,10 +650,10 @@ @deftypefnx {Loadable Function} {@var{p} =} etree (@var{s}, @var{typ})\n\ @deftypefnx {Loadable Function} {[@var{p}, @var{q}] =} etree (@var{s}, @var{typ})\n\ \n\ -Returns the elimination tree for the matrix @var{s}. By default @var{s}\n\ +Returns the elimination tree for the matrix @var{s}. By default @var{s}\n\ is assumed to be symmetric and the symmetric elimination tree is\n\ -returned. The argument @var{typ} controls whether a symmetric or\n\ -column elimination tree is returned. Valid values of @var{typ} are\n\ +returned. The argument @var{typ} controls whether a symmetric or\n\ +column elimination tree is returned. Valid values of @var{typ} are\n\ 'sym' or 'col', for symmetric or column elimination tree respectively\n\ \n\ Called with a second argument, @dfn{etree} also returns the postorder\n\
--- a/src/DLD-FUNCTIONS/conv2.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/conv2.cc Sat Mar 28 13:57:22 2009 -0700 @@ -266,7 +266,7 @@ only parts which do not include zero-padded edges\n\ @end table\n\ \n\ -By default @var{shape} is 'full'. When the third argument is a matrix\n\ +By default @var{shape} is 'full'. When the third argument is a matrix\n\ returns the convolution of the matrix @var{M} by the vector @var{v1}\n\ in the column direction and by vector @var{v2} in the row direction\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/daspk.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/daspk.cc Sat Mar 28 13:57:22 2009 -0700 @@ -231,18 +231,22 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ df df\n\ jac = -- + c ------\n\ dx d xdot\n\ +@end group\n\ @end example\n\ @end ifnottex\n\ \n\ The modified Jacobian function must have the form\n\ \n\ @example\n\ +@group\n\ \n\ @var{jac} = j (@var{x}, @var{xdot}, @var{t}, @var{c})\n\ \n\ +@end group\n\ @end example\n\ \n\ The second and third arguments to @code{daspk} specify the initial\n\
--- a/src/DLD-FUNCTIONS/dasrt.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/dasrt.cc Sat Mar 28 13:57:22 2009 -0700 @@ -275,9 +275,11 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ df df\n\ jac = -- + c ------\n\ dx d xdot\n\ +@end group\n\ @end example\n\ \n\ @end ifnottex\n\ @@ -285,9 +287,11 @@ The modified Jacobian function must have the form\n\ \n\ @example\n\ +@group\n\ \n\ @var{jac} = j (@var{x}, @var{xdot}, @var{t}, @var{c})\n\ \n\ +@end group\n\ @end example\n\ \n\ The optional second argument names a function that defines the\n\
--- a/src/DLD-FUNCTIONS/dassl.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/dassl.cc Sat Mar 28 13:57:22 2009 -0700 @@ -236,18 +236,22 @@ @end iftex\n\ @ifnottex\n\ @example\n\ +@group\n\ df df\n\ jac = -- + c ------\n\ dx d xdot\n\ +@end group\n\ @end example\n\ @end ifnottex\n\ \n\ The modified Jacobian function must have the form\n\ \n\ @example\n\ +@group\n\ \n\ @var{jac} = j (@var{x}, @var{xdot}, @var{t}, @var{c})\n\ \n\ +@end group\n\ @end example\n\ \n\ The second and third arguments to @code{dassl} specify the initial\n\
--- a/src/DLD-FUNCTIONS/dlmread.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/dlmread.cc Sat Mar 28 13:57:22 2009 -0700 @@ -162,7 +162,7 @@ row and column of the data to be read. These values are indexed from zero,\n\ such that the first row corresponds to an index of zero.\n\ \n\ -The @var{range} parameter must be a 4 element vector containing the upper\n\ +The @var{range} parameter must be a 4 element vector containing the upper\n\ left and lower right corner @code{[@var{R0},@var{C0},@var{R1},@var{C1}]} or\n\ a spreadsheet style range such as 'A2..Q15'. The lowest index value is zero.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/dmperm.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/dmperm.cc Sat Mar 28 13:57:22 2009 -0700 @@ -144,8 +144,8 @@ \n\ Called with two or more output arguments, returns the row and column\n\ permutations, such that @code{@var{s} (@var{p}, @var{q})} is in block\n\ -triangular form. The values of @var{r} and @var{s} define the boundaries\n\ -of the blocks. If @var{s} is square then @code{@var{r} == @var{s}}.\n\ +triangular form. The values of @var{r} and @var{s} define the boundaries\n\ +of the blocks. If @var{s} is square then @code{@var{r} == @var{s}}.\n\ \n\ The method used is described in: A. Pothen & C.-J. Fan. Computing the block\n\ triangular form of a sparse matrix. ACM Trans. Math. Software,\n\ @@ -193,11 +193,11 @@ @deftypefn {Loadable Function} {@var{p} =} sprank (@var{s})\n\ \n\ @cindex Structural Rank\n\ -Calculates the structural rank of a sparse matrix @var{s}. Note that\n\ +Calculates the structural rank of a sparse matrix @var{s}. Note that\n\ only the structure of the matrix is used in this calculation based on\n\ -a Dulmage-Mendelsohn permutation to block triangular form. As such the numerical\n\ +a Dulmage-Mendelsohn permutation to block triangular form. As such the numerical\n\ rank of the matrix @var{s} is bounded by @code{sprank (@var{s}) >=\n\ -rank (@var{s})}. Ignoring floating point errors @code{sprank (@var{s}) ==\n\ +rank (@var{s})}. Ignoring floating point errors @code{sprank (@var{s}) ==\n\ rank (@var{s})}.\n\ @seealso{dmperm}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/eigs.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/eigs.cc Sat Mar 28 13:57:22 2009 -0700 @@ -152,7 +152,7 @@ @deftypefnx {Loadable Function} {[@var{v}, @var{d}, @var{flag}]} = eigs (@var{a}, @dots{})\n\ @deftypefnx {Loadable Function} {[@var{v}, @var{d}, @var{flag}]} = eigs (@var{af}, @var{n}, @dots{})\n\ Calculate a limited number of eigenvalues and eigenvectors of @var{a},\n\ -based on a selection criteria. The number eigenvalues and eigenvectors to\n\ +based on a selection criteria. The number eigenvalues and eigenvectors to\n\ calculate is given by @var{k} whose default value is 6.\n\ \n\ By default @code{eigs} solve the equation\n\ @@ -173,7 +173,7 @@ @ifinfo\n\ @code{lambda} is a scalar representing one of the eigenvalues, and @code{v}\n\ @end ifinfo\n\ -is the corresponding eigenvector. If given the positive definite matrix\n\ +is the corresponding eigenvector. If given the positive definite matrix\n\ @var{B} then @code{eigs} solves the general eigenvalue equation\n\ @iftex\n\ @tex\n\ @@ -186,8 +186,8 @@ .\n\ \n\ The argument @var{sigma} determines which eigenvalues are returned.\n\ -@var{sigma} can be either a scalar or a string. When @var{sigma} is a scalar,\n\ -the @var{k} eigenvalues closest to @var{sigma} are returned. If @var{sigma}\n\ +@var{sigma} can be either a scalar or a string. When @var{sigma} is a scalar,\n\ +the @var{k} eigenvalues closest to @var{sigma} are returned. If @var{sigma}\n\ is a string, it must have one of the values\n\ \n\ @table @asis\n\ @@ -221,53 +221,53 @@ @end table\n\ \n\ If @var{opts} is given, it is a structure defining some of the options that\n\ -@code{eigs} should use. The fields of the structure @var{opts} are\n\ +@code{eigs} should use. The fields of the structure @var{opts} are\n\ \n\ @table @code\n\ @item issym\n\ If @var{af} is given, then flags whether the function @var{af} defines a\n\ -symmetric problem. It is ignored if @var{a} is given. The default is false.\n\ +symmetric problem. It is ignored if @var{a} is given. The default is false.\n\ \n\ @item isreal\n\ If @var{af} is given, then flags whether the function @var{af} defines a\n\ -real problem. It is ignored if @var{a} is given. The default is true.\n\ +real problem. It is ignored if @var{a} is given. The default is true.\n\ \n\ @item tol\n\ Defines the required convergence tolerance, given as @code{tol * norm (A)}.\n\ The default is @code{eps}.\n\ \n\ @item maxit\n\ -The maximum number of iterations. The default is 300.\n\ +The maximum number of iterations. The default is 300.\n\ \n\ @item p\n\ -The number of Lanzcos basis vectors to use. More vectors will result in\n\ -faster convergence, but a larger amount of memory. The optimal value of 'p'\n\ -is problem dependent and should be in the range @var{k} to @var{n}. The\n\ +The number of Lanzcos basis vectors to use. More vectors will result in\n\ +faster convergence, but a larger amount of memory. The optimal value of 'p'\n\ +is problem dependent and should be in the range @var{k} to @var{n}. The\n\ default value is @code{2 * @var{k}}.\n\ \n\ @item v0\n\ -The starting vector for the computation. The default is to have @sc{Arpack}\n\ +The starting vector for the computation. The default is to have @sc{Arpack}\n\ randomly generate a starting vector.\n\ \n\ @item disp\n\ -The level of diagnostic printout. If @code{disp} is 0 then there is no\n\ -printout. The default value is 1.\n\ +The level of diagnostic printout. If @code{disp} is 0 then there is no\n\ +printout. The default value is 1.\n\ \n\ @item cholB\n\ -Flag if @code{chol (@var{b})} is passed rather than @var{b}. The default is\n\ +Flag if @code{chol (@var{b})} is passed rather than @var{b}. The default is\n\ false.\n\ \n\ @item permB\n\ The permutation vector of the Cholesky factorization of @var{b} if\n\ -@code{cholB} is true. That is @code{chol ( @var{b} (permB, permB))}. The\n\ +@code{cholB} is true. That is @code{chol ( @var{b} (permB, permB))}. The\n\ default is @code{1:@var{n}}.\n\ \n\ @end table\n\ \n\ It is also possible to represent @var{a} by a function denoted @var{af}.\n\ @var{af} must be followed by a scalar argument @var{n} defining the length\n\ -of the vector argument accepted by @var{af}. @var{af} can be passed either\n\ -as an inline function, function handle or as a string. In the case where\n\ +of the vector argument accepted by @var{af}. @var{af} can be passed either\n\ +as an inline function, function handle or as a string. In the case where\n\ @var{af} is passed as a string, the name of the string defines the function\n\ to use.\n\ \n\ @@ -284,7 +284,7 @@ \n\ @item (A - sigma * I) \\ x\n\ for standard eigenvalue problem, where @code{I} is the identity matrix of\n\ -the same size as @code{A}. If @var{sigma} is zero, this reduces the\n\ +the same size as @code{A}. If @var{sigma} is zero, this reduces the\n\ @code{A \\ x}.\n\ \n\ @item (A - sigma * B) \\ x\n\ @@ -292,20 +292,20 @@ @end table\n\ \n\ The return arguments of @code{eigs} depends on the number of return\n\ -arguments. With a single return argument, a vector @var{d} of length @var{k}\n\ -is returned, represent the @var{k} eigenvalues that have been found. With two\n\ +arguments. With a single return argument, a vector @var{d} of length @var{k}\n\ +is returned, represent the @var{k} eigenvalues that have been found. With two\n\ return arguments, @var{v} is a @var{n}-by-@var{k} matrix whose columns are\n\ -the @var{k} eigenvectors corresponding to the returned eigenvalues. The\n\ +the @var{k} eigenvectors corresponding to the returned eigenvalues. The\n\ eigenvalues themselves are then returned in @var{d} in the form of a\n\ @var{n}-by-@var{k} matrix, where the elements on the diagonal are the\n\ eigenvalues.\n\ \n\ Given a third return argument @var{flag}, @code{eigs} also returns the status\n\ -of the convergence. If @var{flag} is 0, then all eigenvalues have converged,\n\ +of the convergence. If @var{flag} is 0, then all eigenvalues have converged,\n\ otherwise not.\n\ \n\ This function is based on the @sc{Arpack} package, written by R Lehoucq,\n\ -K Maschhoff, D Sorensen and C Yang. For more information see\n\ +K Maschhoff, D Sorensen and C Yang. For more information see\n\ @url{http://www.caam.rice.edu/software/ARPACK/}.\n\ \n\ @end deftypefn\n\
--- a/src/DLD-FUNCTIONS/fft.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/fft.cc Sat Mar 28 13:57:22 2009 -0700 @@ -203,15 +203,15 @@ @deftypefn {Loadable Function} {} fft (@var{a}, @var{n}, @var{dim})\n\ Compute the FFT of @var{a} using subroutines from\n" FFTSRC -". The FFT is calculated along the first non-singleton dimension of the\n\ -array. Thus if @var{a} is a matrix, @code{fft (@var{a})} computes the\n\ +". The FFT is calculated along the first non-singleton dimension of the\n\ +array. Thus if @var{a} is a matrix, @code{fft (@var{a})} computes the\n\ FFT for each column of @var{a}.\n\ \n\ If called with two arguments, @var{n} is expected to be an integer\n\ specifying the number of elements of @var{a} to use, or an empty\n\ -matrix to specify that its value should be ignored. If @var{n} is\n\ +matrix to specify that its value should be ignored. If @var{n} is\n\ larger than the dimension along which the FFT is calculated, then\n\ -@var{a} is resized and padded with zeros. Otherwise, if @var{n} is\n\ +@var{a} is resized and padded with zeros. Otherwise, if @var{n} is\n\ smaller than the dimension along which the FFT is calculated, then\n\ @var{a} is truncated.\n\ \n\ @@ -229,15 +229,15 @@ @deftypefn {Loadable Function} {} ifft (@var{a}, @var{n}, @var{dim})\n\ Compute the inverse FFT of @var{a} using subroutines from\n" FFTSRC -". The inverse FFT is calculated along the first non-singleton dimension\n\ -of the array. Thus if @var{a} is a matrix, @code{fft (@var{a})} computes\n\ +". The inverse FFT is calculated along the first non-singleton dimension\n\ +of the array. Thus if @var{a} is a matrix, @code{fft (@var{a})} computes\n\ the inverse FFT for each column of @var{a}.\n\ \n\ If called with two arguments, @var{n} is expected to be an integer\n\ specifying the number of elements of @var{a} to use, or an empty\n\ -matrix to specify that its value should be ignored. If @var{n} is\n\ +matrix to specify that its value should be ignored. If @var{n} is\n\ larger than the dimension along which the inverse FFT is calculated, then\n\ -@var{a} is resized and padded with zeros. Otherwise, if@var{n} is\n\ +@var{a} is resized and padded with zeros. Otherwise, if@var{n} is\n\ smaller than the dimension along which the inverse FFT is calculated,\n\ then @var{a} is truncated.\n\ \n\
--- a/src/DLD-FUNCTIONS/fftn.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/fftn.cc Sat Mar 28 13:57:22 2009 -0700 @@ -155,9 +155,9 @@ Compute the N-dimensional FFT of @var{a} using subroutines from\n" FFTSRC ". The optional vector argument @var{size} may be used specify the\n\ -dimensions of the array to be used. If an element of @var{size} is\n\ +dimensions of the array to be used. If an element of @var{size} is\n\ smaller than the corresponding dimension, then the dimension is\n\ -truncated prior to performing the FFT. Otherwise if an element\n\ +truncated prior to performing the FFT. Otherwise if an element\n\ of @var{size} is larger than the corresponding dimension @var{a}\n\ is resized and padded with zeros.\n\ @seealso {ifftn, fft, fft2, fftw}\n\ @@ -172,9 +172,9 @@ Compute the inverse N-dimensional FFT of @var{a} using subroutines from\n" FFTSRC ". The optional vector argument @var{size} may be used specify the\n\ -dimensions of the array to be used. If an element of @var{size} is\n\ +dimensions of the array to be used. If an element of @var{size} is\n\ smaller than the corresponding dimension, then the dimension is\n\ -truncated prior to performing the inverse FFT. Otherwise if an element\n\ +truncated prior to performing the inverse FFT. Otherwise if an element\n\ of @var{size} is larger than the corresponding dimension @var{a}\n\ is resized and padded with zeros.\n\ @seealso {fftn, ifft, ifft2, fftw}\n\
--- a/src/DLD-FUNCTIONS/fftw.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/fftw.cc Sat Mar 28 13:57:22 2009 -0700 @@ -40,12 +40,12 @@ @deftypefnx {Loadable Function} {@var{wisdom} =} fftw ('dwisdom')\n\ @deftypefnx {Loadable Function} {@var{wisdom} =} fftw ('dwisdom', @var{wisdom})\n\ \n\ -Manage FFTW wisdom data. Wisdom data can be used to significantly\n\ +Manage FFTW wisdom data. Wisdom data can be used to significantly\n\ accelerate the calculation of the FFTs but implies an initial cost\n\ -in its calculation. When the FFTW libraries are initialized, they read\n\ +in its calculation. When the FFTW libraries are initialized, they read\n\ a system wide wisdom file (typically in @file{/etc/fftw/wisdom}), allowing wisdom\n\ -to be shared between applications other than Octave. Alternatively, the\n\ -@code{fftw} function can be used to import wisdom. For example\n\ +to be shared between applications other than Octave. Alternatively, the\n\ +@code{fftw} function can be used to import wisdom. For example\n\ \n\ @example\n\ @var{wisdom} = fftw ('dwisdom')\n\ @@ -53,7 +53,7 @@ \n\ will save the existing wisdom used by Octave to the string @var{wisdom}.\n\ This string can then be saved to a file and restored using the @code{save}\n\ -and @code{load} commands respectively. This existing wisdom can be reimported\n\ +and @code{load} commands respectively. This existing wisdom can be reimported\n\ as follows\n\ \n\ @example\n\ @@ -64,14 +64,14 @@ \n\ During the calculation of fourier transforms further wisdom is generated.\n\ The fashion in which this wisdom is generated is equally controlled by\n\ -the @code{fftw} function. There are five different manners in which the\n\ +the @code{fftw} function. There are five different manners in which the\n\ wisdom can be treated, these being\n\ \n\ @table @asis\n\ @item 'estimate'\n\ This specifies that no run-time measurement of the optimal means of\n\ calculating a particular is performed, and a simple heuristic is used\n\ -to pick a (probably sub-optimal) plan. The advantage of this method is\n\ +to pick a (probably sub-optimal) plan. The advantage of this method is\n\ that there is little or no overhead in the generation of the plan, which\n\ is appropriate for a fourier transform that will be calculated once.\n\ \n\ @@ -105,9 +105,9 @@ fftw ('planner', @var{method})\n\ @end example\n\ \n\ -Note that calculated wisdom will be lost when restarting Octave. However,\n\ +Note that calculated wisdom will be lost when restarting Octave. However,\n\ the wisdom data can be reloaded if it is saved to a file as described\n\ -above. Saved wisdom files should not be used on different platforms since\n\ +above. Saved wisdom files should not be used on different platforms since\n\ they will not be efficient and the point of calculating the wisdom is lost.\n\ @seealso{fft, ifft, fft2, ifft2, fftn, ifftn}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/filter.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/filter.cc Sat Mar 28 13:57:22 2009 -0700 @@ -314,7 +314,7 @@ @end tex\n\ @end iftex\n\ over the first non-singleton dimension of @var{x} or over @var{dim} if\n\ -supplied. An equivalent form of this equation is:\n\ +supplied. An equivalent form of this equation is:\n\ @iftex\n\ @tex\n\ $$\n\ @@ -364,6 +364,7 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ M\n\ SUM d(k+1) z^(-k)\n\ k=0\n\ @@ -371,6 +372,7 @@ N\n\ 1 + SUM c(k+1) z^(-k)\n\ k=1\n\ +@end group\n\ @end example\n\ @end ifnottex\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/gammainc.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/gammainc.cc Sat Mar 28 13:57:22 2009 -0700 @@ -56,7 +56,7 @@ \n\ @end ifnottex\n\ with the limiting value of 1 as @var{x} approaches infinity.\n\ -The standard notation is @math{P(a,x)}, e.g. Abramowitz and Stegun (6.5.1).\n\ +The standard notation is @math{P(a,x)}, e.g., Abramowitz and Stegun (6.5.1).\n\ \n\ If @var{a} is scalar, then @code{gammainc (@var{x}, @var{a})} is returned\n\ for each element of @var{x} and vice versa.\n\
--- a/src/DLD-FUNCTIONS/gcd.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/gcd.cc Sat Mar 28 13:57:22 2009 -0700 @@ -55,10 +55,10 @@ @deftypefnx {Loadable Function} {[@var{g}, @var{v1}, @dots{}] =} gcd (@var{a1}, @dots{})\n\ \n\ If a single argument is given then compute the greatest common divisor of\n\ -the elements of this argument. Otherwise if more than one argument is\n\ -given all arguments must be the same size or scalar. In this case the\n\ -greatest common divisor is calculated for element individually. All\n\ -elements must be integers. For example,\n\ +the elements of this argument. Otherwise if more than one argument is\n\ +given all arguments must be the same size or scalar. In this case the\n\ +greatest common divisor is calculated for element individually. All\n\ +elements must be integers. For example,\n\ \n\ @example\n\ @group\n\
--- a/src/DLD-FUNCTIONS/getpwent.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/getpwent.cc Sat Mar 28 13:57:22 2009 -0700 @@ -72,7 +72,7 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {@var{pw_struct} =} getpwent ()\n\ Return a structure containing an entry from the password database,\n\ -opening it if necessary. Once the end of the data has been reached,\n\ +opening it if necessary. Once the end of the data has been reached,\n\ @code{getpwent} returns 0.\n\ @end deftypefn") {
--- a/src/DLD-FUNCTIONS/hex2num.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/hex2num.cc Sat Mar 28 13:57:22 2009 -0700 @@ -43,8 +43,10 @@ number.\n\ \n\ @example\n\ +@group\n\ hex2num ([\"4005bf0a8b145769\";\"4024000000000000\"])\n\ @result{} [2.7183; 10.000]\n\ +@end group\n\ @end example\n\ @seealso{num2hex, hex2dec, dec2hex}\n\ @end deftypefn") @@ -125,6 +127,7 @@ string of the IEEE 754 representation of the number. For example\n\ \n\ @example\n\ +@group\n\ num2hex ([-1, 1, e, Inf, NaN, NA]);\n\ @result{} \"bff0000000000000\n\ 3ff0000000000000\n\ @@ -132,6 +135,7 @@ 7ff0000000000000\n\ fff8000000000000\n\ 7ff00000000007a2\"\n\ +@end group\n\ @end example\n\ @seealso{hex2num, hex2dec, dec2hex}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/inv.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/inv.cc Sat Mar 28 13:57:22 2009 -0700 @@ -47,7 +47,7 @@ \n\ If called with a sparse matrix, then in general @var{x} will be a full\n\ matrix, and so if possible forming the inverse of a sparse matrix should\n\ -be avoided. It is significantly more accurate and faster to do\n\ +be avoided. It is significantly more accurate and faster to do\n\ @code{@var{y} = @var{a} \\ @var{b}}, rather than\n\ @code{@var{y} = inv (@var{a}) * @var{b}}.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/lookup.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/lookup.cc Sat Mar 28 13:57:22 2009 -0700 @@ -124,15 +124,15 @@ (unless a conversion occurs due to non-numeric or unequal types).\n\ \n\ @var{table} and @var{y} can also be cell arrays of strings\n\ -(or @var{y} can be a single string). In this case, string lookup\n\ +(or @var{y} can be a single string). In this case, string lookup\n\ is performed using lexicographical comparison.\n\ \n\ If @var{opts} is specified, it shall be a string with letters indicating\n\ additional options.\n\ For numeric lookup, 'l' in @var{opts} indicates that\n\ -the leftmost subinterval shall be extended to infinity (i.e. all indices\n\ +the leftmost subinterval shall be extended to infinity (i.e., all indices\n\ at least 1), and 'r' indicates that the rightmost subinterval shall be\n\ -extended to infinity (i.e. all indices at most n-1).\n\ +extended to infinity (i.e., all indices at most n-1).\n\ \n\ For string lookup, 'i' indicates case-insensitive comparison.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/lsode.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/lsode.cc Sat Mar 28 13:57:22 2009 -0700 @@ -174,9 +174,11 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ dx\n\ -- = f(x, t)\n\ dt\n\ +@end group\n\ @end example\n\ \n\ with\n\ @@ -233,6 +235,7 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ | df_1 df_1 df_1 |\n\ | ---- ---- ... ---- |\n\ | dx_1 dx_2 dx_N |\n\ @@ -248,6 +251,7 @@ | df_N df_N df_N |\n\ | ---- ---- ... ---- |\n\ | dx_1 dx_2 dx_N |\n\ +@end group\n\ @end example\n\ \n\ @end ifnottex\n\
--- a/src/DLD-FUNCTIONS/lu.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/lu.cc Sat Mar 28 13:57:22 2009 -0700 @@ -72,7 +72,7 @@ @deftypefnx {Loadable Function} {@var{y} =} lu (@dots{})\n\ @deftypefnx {Loadable Function} {[@dots{}] =} lu (@dots{}, 'vector')\n\ @cindex LU decomposition\n\ -Compute the LU decomposition of @var{a}. If @var{a} is full subroutines from\n\ +Compute the LU decomposition of @var{a}. If @var{a} is full subroutines from\n\ @sc{Lapack} are used and if @var{a} is sparse then UMFPACK is used. The\n\ result is returned in a permuted form, according to the optional return\n\ value @var{p}. For example, given the matrix @code{a = [1, 2; 3, 4]},\n\ @@ -85,6 +85,7 @@ returns\n\ \n\ @example\n\ +@group\n\ l =\n\ \n\ 1.00000 0.00000\n\ @@ -99,13 +100,14 @@ \n\ 0 1\n\ 1 0\n\ +@end group\n\ @end example\n\ \n\ The matrix is not required to be square.\n\ \n\ Called with two or three output arguments and a spare input matrix,\n\ then @dfn{lu} does not attempt to perform sparsity preserving column\n\ -permutations. Called with a fourth output argument, the sparsity\n\ +permutations. Called with a fourth output argument, the sparsity\n\ preserving column transformation @var{Q} is returned, such that\n\ @code{@var{p} * @var{a} * @var{q} = @var{l} * @var{u}}.\n\ \n\ @@ -115,11 +117,11 @@ This typically leads to a sparser and more stable factorsation.\n\ \n\ An additional input argument @var{thres}, that defines the pivoting\n\ -threshold can be given. @var{thres} can be a scalar, in which case\n\ +threshold can be given. @var{thres} can be a scalar, in which case\n\ it defines UMFPACK pivoting tolerance for both symmetric and unsymmetric\n\ -cases. If @var{thres} is a two element vector, then the first element\n\ +cases. If @var{thres} is a two element vector, then the first element\n\ defines the pivoting tolerance for the unsymmetric UMFPACK pivoting\n\ -strategy and the second the symmetric strategy. By default, the values\n\ +strategy and the second the symmetric strategy. By default, the values\n\ defined by @code{spparms} are used and are by default @code{[0.1, 0.001]}.\n\ \n\ Given the string argument 'vector', @dfn{lu} returns the values of @var{p}\n\ @@ -130,7 +132,7 @@ With two output arguments, returns the permuted forms of the upper and\n\ lower triangular matrices, such that @code{@var{a} = @var{l} * @var{u}}.\n\ With one output argument @var{y}, then the matrix returned by the @sc{Lapack}\n\ -routines is returned. If the input matrix is sparse then the matrix @var{l}\n\ +routines is returned. If the input matrix is sparse then the matrix @var{l}\n\ is embedded into @var{u} to give a return value similar to the full case.\n\ For both full and sparse matrices, @dfn{lu} looses the permutation\n\ information.\n\
--- a/src/DLD-FUNCTIONS/luinc.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/luinc.cc Sat Mar 28 13:57:22 2009 -0700 @@ -48,47 +48,47 @@ is determined by the second argument to @dfn{luinc}.\n\ \n\ Called with a second argument of '0', the zero-level incomplete\n\ -LU factorization is produced. This creates a factorization of @var{a}\n\ +LU factorization is produced. This creates a factorization of @var{a}\n\ where the position of the non-zero arguments correspond to the same\n\ positions as in the matrix @var{a}.\n\ \n\ Alternatively, the fill-in of the incomplete LU factorization can\n\ be controlled through the variable @var{droptol} or the structure\n\ -@var{opts}. The UMFPACK multifrontal factorization code by Tim A.\n\ +@var{opts}. The UMFPACK multifrontal factorization code by Tim A.\n\ Davis is used for the incomplete LU factorization, (availability\n\ @url{http://www.cise.ufl.edu/research/sparse/umfpack/})\n\ \n\ @var{droptol} determines the values below which the values in the LU\n\ -factorization are dropped and replaced by zero. It must be a positive\n\ +factorization are dropped and replaced by zero. It must be a positive\n\ scalar, and any values in the factorization whose absolute value are\n\ less than this value are dropped, expect if leaving them increase the\n\ -sparsity of the matrix. Setting @var{droptol} to zero results in a\n\ +sparsity of the matrix. Setting @var{droptol} to zero results in a\n\ complete LU factorization which is the default.\n\ \n\ @var{opts} is a structure containing one or more of the fields\n\ \n\ @table @code\n\ @item droptol\n\ -The drop tolerance as above. If @var{opts} only contains @code{droptol}\n\ +The drop tolerance as above. If @var{opts} only contains @code{droptol}\n\ then this is equivalent to using the variable @var{droptol}.\n\ \n\ @item milu\n\ A logical variable flagging whether to use the modified incomplete LU\n\ -factorization. In the case that @code{milu} is true, the dropped values\n\ +factorization. In the case that @code{milu} is true, the dropped values\n\ are subtracted from the diagonal of the matrix U of the factorization.\n\ The default is @code{false}.\n\ \n\ @item udiag\n\ A logical variable that flags whether zero elements on the diagonal of U\n\ should be replaced with @var{droptol} to attempt to avoid singular\n\ -factors. The default is @code{false}.\n\ +factors. The default is @code{false}.\n\ \n\ @item thresh\n\ -Defines the pivot threshold in the interval [0,1]. Values outside that\n\ +Defines the pivot threshold in the interval [0,1]. Values outside that\n\ range are ignored.\n\ @end table\n\ \n\ -All other fields in @var{opts} are ignored. The outputs from @dfn{luinc}\n\ +All other fields in @var{opts} are ignored. The outputs from @dfn{luinc}\n\ are the same as for @dfn{lu}.\n\ \n\ Given the string argument 'vector', @dfn{luinc} returns the values of @var{p}\n\
--- a/src/DLD-FUNCTIONS/matrix_type.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/matrix_type.cc Sat Mar 28 13:57:22 2009 -0700 @@ -43,10 +43,10 @@ @deftypefnx {Loadable Function} {@var{a} =} matrix_type (@var{a}, 'upper', @var{perm})\n\ @deftypefnx {Loadable Function} {@var{a} =} matrix_type (@var{a}, 'lower', @var{perm})\n\ @deftypefnx {Loadable Function} {@var{a} =} matrix_type (@var{a}, 'banded', @var{nl}, @var{nu})\n\ -Identify the matrix type or mark a matrix as a particular type. This allows rapid\n\ -for solutions of linear equations involving @var{a} to be performed. Called with a\n\ +Identify the matrix type or mark a matrix as a particular type. This allows rapid\n\ +for solutions of linear equations involving @var{a} to be performed. Called with a\n\ single argument, @code{matrix_type} returns the type of the matrix and caches it for\n\ -future use. Called with more than one argument, @code{matrix_type} allows the type\n\ +future use. Called with more than one argument, @code{matrix_type} allows the type\n\ of the matrix to be defined.\n\ \n\ The possible matrix types depend on whether the matrix is full or sparse, and can be\n\ @@ -63,28 +63,28 @@ Probable full positive definite matrix.\n\ \n\ @item 'diagonal'\n\ -Diagonal Matrix. (Sparse matrices only)\n\ +Diagonal Matrix. (Sparse matrices only)\n\ \n\ @item 'permuted diagonal'\n\ -Permuted Diagonal matrix. The permutation does not need to be specifically\n\ -indicated, as the structure of the matrix explicitly gives this. (Sparse matrices\n\ +Permuted Diagonal matrix. The permutation does not need to be specifically\n\ +indicated, as the structure of the matrix explicitly gives this. (Sparse matrices\n\ only)\n\ \n\ @item 'upper'\n\ -Upper triangular. If the optional third argument @var{perm} is given, the matrix is\n\ +Upper triangular. If the optional third argument @var{perm} is given, the matrix is\n\ assumed to be a permuted upper triangular with the permutations defined by the\n\ vector @var{perm}.\n\ \n\ @item 'lower'\n\ -Lower triangular. If the optional third argument @var{perm} is given, the matrix is\n\ +Lower triangular. If the optional third argument @var{perm} is given, the matrix is\n\ assumed to be a permuted lower triangular with the permutations defined by the\n\ vector @var{perm}.\n\ \n\ @item 'banded'\n\ @itemx 'banded positive definite'\n\ Banded matrix with the band size of @var{nl} below the diagonal and @var{nu} above\n\ -it. If @var{nl} and @var{nu} are 1, then the matrix is tridiagonal and treated\n\ -with specialized code. In addition the matrix can be marked as probably a\n\ +it. If @var{nl} and @var{nu} are 1, then the matrix is tridiagonal and treated\n\ +with specialized code. In addition the matrix can be marked as probably a\n\ positive definite (Sparse matrices only)\n\ \n\ @item 'singular'\n\ @@ -93,17 +93,17 @@ @end table\n\ \n\ Note that the matrix type will be discovered automatically on the first attempt to\n\ -solve a linear equation involving @var{a}. Therefore @code{matrix_type} is only\n\ -useful to give Octave hints of the matrix type. Incorrectly defining the\n\ +solve a linear equation involving @var{a}. Therefore @code{matrix_type} is only\n\ +useful to give Octave hints of the matrix type. Incorrectly defining the\n\ matrix type will result in incorrect results from solutions of linear equations,\n\ and so it is entirely the responsibility of the user to correctly identify the\n\ matrix type.\n\ \n\ Also the test for positive definiteness is a low-cost test for a hermitian\n\ -matrix with a real positive diagonal. This does not guarantee that the matrix\n\ -is positive definite, but only that it is a probable candidate. When such a\n\ +matrix with a real positive diagonal. This does not guarantee that the matrix\n\ +is positive definite, but only that it is a probable candidate. When such a\n\ matrix is factorized, a Cholesky factorization is first attempted, and if\n\ -that fails the matrix is then treated with an LU factorization. Once the\n\ +that fails the matrix is then treated with an LU factorization. Once the\n\ matrix has been factorized, @code{matrix_type} will return the correct\n\ classification of the matrix.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/max.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/max.cc Sat Mar 28 13:57:22 2009 -0700 @@ -691,7 +691,7 @@ @cindex Utility Functions\n\ For a vector argument, return the minimum value. For a matrix\n\ argument, return the minimum value from each column, as a row\n\ -vector, or over the dimension @var{dim} if defined. For two matrices\n\ +vector, or over the dimension @var{dim} if defined. For two matrices\n\ (or a matrix and scalar), return the pair-wise minimum.\n\ Thus,\n\ \n\ @@ -717,7 +717,7 @@ \n\ If called with one input and two output arguments,\n\ @code{min} also returns the first index of the\n\ -minimum value(s). Thus,\n\ +minimum value(s). Thus,\n\ \n\ @example\n\ @group\n\ @@ -765,7 +765,7 @@ @cindex Utility Functions\n\ For a vector argument, return the maximum value. For a matrix\n\ argument, return the maximum value from each column, as a row\n\ -vector, or over the dimension @var{dim} if defined. For two matrices\n\ +vector, or over the dimension @var{dim} if defined. For two matrices\n\ (or a matrix and scalar), return the pair-wise maximum.\n\ Thus,\n\ \n\ @@ -791,7 +791,7 @@ \n\ If called with one input and two output arguments,\n\ @code{max} also returns the first index of the\n\ -maximum value(s). Thus,\n\ +maximum value(s). Thus,\n\ \n\ @example\n\ @group\n\ @@ -919,7 +919,7 @@ @deftypefn {Loadable Function} {} cummin (@var{x}, @var{dim})\n\ @deftypefnx {Loadable Function} {[@var{w}, @var{iw}] =} cummin (@var{x})\n\ @cindex Utility Functions\n\ -Return the cumulative minimum values. That means, the call\n\ +Return the cumulative minimum values. That means, the call\n\ @example\n\ [w, iw] = cummin (x, dim)\n\ @end example\n\ @@ -927,13 +927,15 @@ @noindent\n\ is equivalent to the following code:\n\ @example\n\ +@group\n\ w = iw = zeros (size (x));\n\ idxw = idxx = repmat (@{':'@}, 1, ndims (x));\n\ for i = 1:size (x, dim)\n\ idxw@{dim@} = i; idxx@{dim@} = 1:i;\n\ - [w(idxw@{:@}), iw(idxw@{:@})] =\ + [w(idxw@{:@}), iw(idxw@{:@})] =\\n\ min(x(idxx@{:@}), [], dim);\n\ endfor\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -950,7 +952,7 @@ @deftypefn {Loadable Function} {} cummax (@var{x}, @var{dim})\n\ @deftypefnx {Loadable Function} {[@var{w}, @var{iw}] =} cummax (@var{x})\n\ @cindex Utility Functions\n\ -Return the cumulative maximum values. That means, the call\n\ +Return the cumulative maximum values. That means, the call\n\ @example\n\ [w, iw] = cummax (x, dim)\n\ @end example\n\ @@ -958,13 +960,15 @@ @noindent\n\ is equivalent to the following code:\n\ @example\n\ +@group\n\ w = iw = zeros (size (x));\n\ idxw = idxx = repmat (@{':'@}, 1, ndims (x));\n\ for i = 1:size (x, dim)\n\ idxw@{dim@} = i; idxx@{dim@} = 1:i;\n\ - [w(idxw@{:@}), iw(idxw@{:@})] =\ + [w(idxw@{:@}), iw(idxw@{:@})] =\\n\ max(x(idxx@{:@}), [], dim);\n\ endfor\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\
--- a/src/DLD-FUNCTIONS/md5sum.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/md5sum.cc Sat Mar 28 13:57:22 2009 -0700 @@ -40,7 +40,7 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {} md5sum (@var{file})\n\ @deftypefnx {Loadable Function} {} md5sum (@var{str}, @var{opt})\n\ -Calculates the MD5 sum of the file @var{file}. If the second parameter\n\ +Calculates the MD5 sum of the file @var{file}. If the second parameter\n\ @var{opt} exists and is true, then calculate the MD5 sum of the\n\ string @var{str}.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/pinv.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/pinv.cc Sat Mar 28 13:57:22 2009 -0700 @@ -41,7 +41,7 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {} pinv (@var{x}, @var{tol})\n\ Return the pseudoinverse of @var{x}. Singular values less than\n\ -@var{tol} are ignored. \n\ +@var{tol} are ignored. \n\ \n\ If the second argument is omitted, it is assumed that\n\ \n\
--- a/src/DLD-FUNCTIONS/qr.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/qr.cc Sat Mar 28 13:57:22 2009 -0700 @@ -100,6 +100,7 @@ returns\n\ \n\ @example\n\ +@group\n\ q =\n\ \n\ -0.31623 -0.94868\n\ @@ -109,6 +110,7 @@ \n\ -3.16228 -4.42719\n\ 0.00000 -0.63246\n\ +@end group\n\ @end example\n\ \n\ The @code{qr} factorization has applications in the solution of least\n\ @@ -164,6 +166,7 @@ returns\n\ \n\ @example\n\ +@group\n\ q = \n\ \n\ -0.44721 -0.89443\n\ @@ -178,6 +181,7 @@ \n\ 0 1\n\ 1 0\n\ +@end group\n\ @end example\n\ \n\ The permuted @code{qr} factorization @code{[q, r, p] = qr (a)}\n\ @@ -185,22 +189,24 @@ @code{span (a)}.\n\ \n\ If the matrix @var{a} is sparse, then compute the sparse QR factorization\n\ -of @var{a}, using @sc{CSparse}. As the matrix @var{Q} is in general a full\n\ +of @var{a}, using @sc{CSparse}. As the matrix @var{Q} is in general a full\n\ matrix, this function returns the @var{Q}-less factorization @var{r} of\n\ @var{a}, such that @code{@var{r} = chol (@var{a}' * @var{a})}.\n\ \n\ If the final argument is the scalar @code{0} and the number of rows is\n\ larger than the number of columns, then an economy factorization is\n\ -returned. That is @var{r} will have only @code{size (@var{a},1)} rows.\n\ +returned. That is @var{r} will have only @code{size (@var{a},1)} rows.\n\ \n\ If an additional matrix @var{b} is supplied, then @code{qr} returns\n\ -@var{c}, where @code{@var{c} = @var{q}' * @var{b}}. This allows the\n\ +@var{c}, where @code{@var{c} = @var{q}' * @var{b}}. This allows the\n\ least squares approximation of @code{@var{a} \\ @var{b}} to be calculated\n\ as\n\ \n\ @example\n\ +@group\n\ [@var{c},@var{r}] = spqr (@var{a},@var{b})\n\ @var{x} = @var{r} \\ @var{c}\n\ +@end group\n\ @end example\n\ @end deftypefn") { @@ -784,7 +790,7 @@ @var{R}@tie{}upper trapezoidal, return the QR@tie{}factorization\n\ of @w{@var{A} + @var{u}*@var{v}'}, where @var{u} and @var{v} are\n\ column vectors (rank-1 update) or matrices with equal number of columns\n\ -(rank-k update). Notice that the latter case is done as a sequence of rank-1 updates;\n\ +(rank-k update). Notice that the latter case is done as a sequence of rank-1 updates;\n\ thus, for k large enough, it will be both faster and more accurate to recompute\n\ the factorization from scratch.\n\ \n\ @@ -1178,9 +1184,9 @@ Given a QR@tie{}factorization of a real or complex matrix\n\ @w{@var{A} = @var{Q}*@var{R}}, @var{Q}@tie{}unitary and\n\ @var{R}@tie{}upper trapezoidal, return the QR@tie{}factorization of\n\ -@w{[A(:,1:j-1) A(:,j+1:n)]}, i.e. @var{A} with one column deleted\n\ +@w{[A(:,1:j-1) A(:,j+1:n)]}, i.e., @var{A} with one column deleted\n\ (if @var{orient} is \"col\"), or the QR@tie{}factorization of\n\ -@w{[A(1:j-1,:);A(:,j+1:n)]}, i.e. @var{A} with one row deleted (if\n\ +@w{[A(1:j-1,:);A(:,j+1:n)]}, i.e., @var{A} with one row deleted (if\n\ @var{orient} is \"row\").\n\ \n\ The default value of @var{orient} is \"col\".\n\ @@ -1431,7 +1437,7 @@ of @w{@var{A}(:,p)}, where @w{p} is the permutation @*\n\ @code{p = [1:i-1, shift(i:j, 1), j+1:n]} if @w{@var{i} < @var{j}} @*\n\ or @*\n\ -@code{p = [1:j-1, shift(j:i,-1), i+1:n]} if @w{@var{j} < @var{i}}. @*\n\ +@code{p = [1:j-1, shift(j:i,-1), i+1:n]} if @w{@var{j} < @var{i}}. @*\n\ \n\ @seealso{qr, qrinsert, qrdelete}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/quad.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/quad.cc Sat Mar 28 13:57:22 2009 -0700 @@ -178,7 +178,7 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {[@var{v}, @var{ier}, @var{nfun}, @var{err}] =} quad (@var{f}, @var{a}, @var{b}, @var{tol}, @var{sing})\n\ Integrate a nonlinear function of one variable using Quadpack.\n\ -The first argument is the name of the function, the function handle or\n\ +The first argument is the name of the function, the function handle or\n\ the inline function to call to compute the value of the integrand. It\n\ must have the form\n\ \n\ @@ -197,7 +197,7 @@ absolute tolerance, and the second element is the desired relative\n\ tolerance. To choose a relative test only, set the absolute\n\ tolerance to zero. To choose an absolute test only, set the relative\n\ -tolerance to zero. \n\ +tolerance to zero. \n\ \n\ The optional argument @var{sing} is a vector of values at which the\n\ integrand is known to be singular.\n\
--- a/src/DLD-FUNCTIONS/qz.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/qz.cc Sat Mar 28 13:57:22 2009 -0700 @@ -208,7 +208,7 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {@var{lambda} =} qz (@var{a}, @var{b})\n\ Generalized eigenvalue problem @math{A x = s B x},\n\ -@var{QZ} decomposition. There are three ways to call this function:\n\ +@var{QZ} decomposition. There are three ways to call this function:\n\ @enumerate\n\ @item @code{lambda = qz(A,B)}\n\ \n\ @@ -254,7 +254,7 @@ the generalized eigenvectors @var{V}, @var{W}, nor the orthogonal matrix @var{Q}.\n\ @table @var\n\ @item opt\n\ -for ordering eigenvalues of the GEP pencil. The leading block\n\ +for ordering eigenvalues of the GEP pencil. The leading block\n\ of the revised pencil contains all eigenvalues that satisfy:\n\ @table @code\n\ @item \"N\"\n\ @@ -273,12 +273,12 @@ @item \"+\"\n\ = nonnegative real part: leading block has all eigenvalues\n\ in the closed right half-plane\n\ -@end table\n\ +@end table\n\ @end table\n\ @end enumerate\n\ \n\ Note: qz performs permutation balancing, but not scaling (see balance).\n\ -Order of output arguments was selected for compatibility with MATLAB\n\ +Order of output arguments was selected for compatibility with @sc{matlab}\n\ \n\ @seealso{balance, eig, schur}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/rand.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/rand.cc Sat Mar 28 13:57:22 2009 -0700 @@ -324,7 +324,7 @@ v = rand (\"state\")\n\ @end example\n\ \n\ -This returns a column vector @var{v} of length 625. Later, you can\n\ +This returns a column vector @var{v} of length 625. Later, you can\n\ restore the random number generator to the state @var{v}\n\ using the form\n\ \n\ @@ -363,7 +363,7 @@ rand (\"seed\", val)\n\ @end example\n\ \n\ -which sets the seed of the generator to @var{val}. The seed of the\n\ +which sets the seed of the generator to @var{val}. The seed of the\n\ generator can be queried with\n\ \n\ @example\n\ @@ -636,8 +636,10 @@ @end example\n\ @item @code{beta (a, b)} for @code{a > -1}, @code{b > -1}\n\ @example\n\ +@group\n\ r1 = randg (a, 1)\n\ r = r1 / (r1 + randg (b, 1))\n\ +@end group\n\ @end example\n\ @item @code{Erlang (a, n)}\n\ @example\n\ @@ -668,14 +670,18 @@ @item non-central @code{chisq (df, L)}, for @code{df >= 0} and @code{L > 0}\n\ (use chisq if @code{L = 0})\n\ @example\n\ +@group\n\ r = randp (L / 2)\n\ r(r > 0) = 2 * randg (r(r > 0))\n\ r(df > 0) += 2 * randg (df(df > 0)/2)\n\ +@end group\n\ @end example\n\ @item @code{Dirichlet (a1, @dots{} ak)}\n\ @example\n\ +@group\n\ r = (randg (a1), @dots{}, randg (ak))\n\ r = r / sum (r)\n\ +@end group\n\ @end example\n\ @end table\n\ @seealso{rand, randn, rande, randp}\n\ @@ -869,7 +875,7 @@ @deftypefnx {Loadable Function} {} randp (@var{l}, @var{n}, @var{m})\n\ @deftypefnx {Loadable Function} {} randp (\"state\", @var{x})\n\ @deftypefnx {Loadable Function} {} randp (\"seed\", @var{x})\n\ -Return a matrix with Poisson distributed random elements with mean value parameter given by the first argument, @var{l}. The arguments\n\ +Return a matrix with Poisson distributed random elements with mean value parameter given by the first argument, @var{l}. The arguments\n\ are handled the same as the arguments for @code{rand}, except for the\n\ argument @var{l}.\n\ \n\
--- a/src/DLD-FUNCTIONS/rcond.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/rcond.cc Sat Mar 28 13:57:22 2009 -0700 @@ -34,10 +34,10 @@ "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {@var{c} =} rcond (@var{a})\n\ Compute the 1-norm estimate of the reciprocal condition as returned\n\ -by LAPACK. If the matrix is well-conditioned then @var{c} will be near\n\ +by LAPACK. If the matrix is well-conditioned then @var{c} will be near\n\ 1 and if the matrix is poorly conditioned it will be close to zero.\n\ \n\ -The matrix @var{a} must not be sparse. If the matrix is sparse then\n\ +The matrix @var{a} must not be sparse. If the matrix is sparse then\n\ @code{condest (@var{a})} or @code{rcond (full (@var{a}))} should be used\n\ instead.\n\ @seealso{inv}\n\
--- a/src/DLD-FUNCTIONS/regexp.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/regexp.cc Sat Mar 28 13:57:22 2009 -0700 @@ -1545,9 +1545,11 @@ The replacement can contain @code{$i}, which substitutes\n\ for the ith set of parentheses in the match string. E.g.,\n\ @example\n\ +@group\n\ \n\ regexprep(\"Bill Dunn\",'(\\w+) (\\w+)','$2, $1')\n\ \n\ +@end group\n\ @end example\n\ returns \"Dunn, Bill\"\n\ \n\
--- a/src/DLD-FUNCTIONS/sparse.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/sparse.cc Sat Mar 28 13:57:22 2009 -0700 @@ -68,7 +68,7 @@ Given the integer index vectors @var{i} and @var{j}, a 1-by-@code{nnz} vector\n\ of real of complex values @var{sv}, overall dimensions @var{m} and @var{n}\n\ of the sparse matrix. The argument @code{nzmax} is ignored but accepted for\n\ -compatibility with @sc{Matlab}. If @var{m} or @var{n} are not specified their\n\ +compatibility with @sc{matlab}. If @var{m} or @var{n} are not specified their\n\ values are derived from the maximum index in the vectors @var{i} and @var{j}\n\ as given by @code{@var{m} = max (@var{i})}, @code{@var{n} = max (@var{j})}.\n\ \n\
--- a/src/DLD-FUNCTIONS/spparms.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/spparms.cc Sat Mar 28 13:57:22 2009 -0700 @@ -44,8 +44,8 @@ @deftypefnx {Loadable Function} { } spparms ('tight')\n\ @deftypefnx {Loadable Function} { } spparms (@var{key}, @var{val})\n\ Sets or displays the parameters used by the sparse solvers and factorization\n\ -functions. The first four calls above get information about the current\n\ -settings, while the others change the current settings. The parameters are\n\ +functions. The first four calls above get information about the current\n\ +settings, while the others change the current settings. The parameters are\n\ stored as pairs of keys and values, where the values are all floats and the\n\ keys are one of the following strings:\n\ \n\ @@ -53,17 +53,17 @@ @item spumoni\n\ Printing level of debugging information of the solvers (default 0)\n\ @item ths_rel\n\ -Included for compatibility. Not used. (default 1)\n\ +Included for compatibility. Not used. (default 1)\n\ @item ths_abs\n\ -Included for compatibility. Not used. (default 1)\n\ +Included for compatibility. Not used. (default 1)\n\ @item exact_d\n\ -Included for compatibility. Not used. (default 0)\n\ +Included for compatibility. Not used. (default 0)\n\ @item supernd\n\ -Included for compatibility. Not used. (default 3)\n\ +Included for compatibility. Not used. (default 3)\n\ @item rreduce\n\ -Included for compatibility. Not used. (default 3)\n\ +Included for compatibility. Not used. (default 3)\n\ @item wh_frac\n\ -Included for compatibility. Not used. (default 0.5)\n\ +Included for compatibility. Not used. (default 0.5)\n\ @item autommd\n\ Flag whether the LU/QR and the '\\' and '/' operators will automatically\n\ use the sparsity preserving mmd functions (default 1)\n\ @@ -83,8 +83,8 @@ @end table\n\ \n\ The value of individual keys can be set with @code{spparms (@var{key},\n\ -@var{val})}. The default values can be restored with the special keyword\n\ -'defaults'. The special keyword 'tight' can be used to set the mmd solvers\n\ +@var{val})}. The default values can be restored with the special keyword\n\ +'defaults'. The special keyword 'tight' can be used to set the mmd solvers\n\ to attempt for a sparser solution at the potential cost of longer running\n\ time.\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/sqrtm.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/sqrtm.cc Sat Mar 28 13:57:22 2009 -0700 @@ -175,7 +175,7 @@ @deftypefn {Loadable Function} {[@var{result}, @var{error_estimate}] =} sqrtm (@var{a})\n\ Compute the matrix square root of the square matrix @var{a}.\n\ \n\ -Ref: Nicholas J. Higham. A new sqrtm for MATLAB. Numerical Analysis\n\ +Ref: Nicholas J. Higham. A new sqrtm for @sc{matlab}. Numerical Analysis\n\ Report No. 336, Manchester Centre for Computational Mathematics,\n\ Manchester, England, January 1999.\n\ @seealso{expm, logm}\n\
--- a/src/DLD-FUNCTIONS/svd.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/svd.cc Sat Mar 28 13:57:22 2009 -0700 @@ -77,11 +77,13 @@ returns\n\ \n\ @example\n\ +@group\n\ ans =\n\ \n\ 1.4083189\n\ 0.1223271\n\ 0.0026873\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -95,6 +97,7 @@ returns\n\ \n\ @example\n\ +@group\n\ u =\n\ \n\ -0.82704 0.54745 0.12766\n\ @@ -112,6 +115,7 @@ -0.82704 0.54745 0.12766\n\ -0.45986 -0.52829 -0.71375\n\ -0.32330 -0.64901 0.68867\n\ +@end group\n\ @end example\n\ \n\ If given a second argument, @code{svd} returns an economy-sized\n\
--- a/src/DLD-FUNCTIONS/symbfact.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/symbfact.cc Sat Mar 28 13:57:22 2009 -0700 @@ -55,7 +55,7 @@ \n\ @table @code\n\ @item sym\n\ -Factorize @var{s}. This is the default.\n\ +Factorize @var{s}. This is the default.\n\ \n\ @item col\n\ Factorize @code{@var{s}' * @var{s}}.\n\ @@ -68,7 +68,7 @@ @item @var{mode}\n\ The default is to return the Cholesky factorization for @var{r}, and if\n\ @var{mode} is 'L', the conjugate transpose of the Cholesky factorization\n\ -is returned. The conjugate transpose version is faster and uses less\n\ +is returned. The conjugate transpose version is faster and uses less\n\ memory, but returns the same values for @var{count}, @var{h}, @var{parent}\n\ and @var{post} outputs.\n\ @end table\n\
--- a/src/DLD-FUNCTIONS/tsearch.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/tsearch.cc Sat Mar 28 13:57:22 2009 -0700 @@ -60,9 +60,9 @@ DEFUN_DLD (tsearch, args, , "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {@var{idx} =} tsearch (@var{x}, @var{y}, @var{t}, @var{xi}, @var{yi})\n\ -Searches for the enclosing Delaunay convex hull. For @code{@var{t} =\n\ +Searches for the enclosing Delaunay convex hull. For @code{@var{t} =\n\ delaunay (@var{x}, @var{y})}, finds the index in @var{t} containing the\n\ -points @code{(@var{xi}, @var{yi})}. For points outside the convex hull,\n\ +points @code{(@var{xi}, @var{yi})}. For points outside the convex hull,\n\ @var{idx} is NaN.\n\ @seealso{delaunay, delaunayn}\n\ @end deftypefn")
--- a/src/DLD-FUNCTIONS/urlwrite.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/DLD-FUNCTIONS/urlwrite.cc Sat Mar 28 13:57:22 2009 -0700 @@ -209,8 +209,10 @@ @var{localfile}. For example,\n\ \n\ @example\n\ +@group\n\ urlwrite (\"ftp://ftp.octave.org/pub/octave/README\", \n\ \"README.txt\");\n\ +@end group\n\ @end example\n\ \n\ The full path of the downloaded file is returned in @var{f}. The\n\ @@ -224,8 +226,10 @@ the URL, for example:\n\ \n\ @example\n\ +@group\n\ urlwrite (\"http://username:password@@example.com/file.txt\",\n\ \"file.txt\");\n\ +@end group\n\ @end example\n\ \n\ GET and POST requests can be specified by @var{method} and @var{param}.\n\ @@ -234,8 +238,10 @@ For example:\n\ \n\ @example\n\ +@group\n\ urlwrite (\"http://www.google.com/search\", \"search.html\",\n\ \"get\", @{\"query\", \"octave\"@});\n\ +@end group\n\ @end example\n\ @seealso{urlread}\n\ @end deftypefn") @@ -391,8 +397,10 @@ For example,\n\ \n\ @example\n\ +@group\n\ s = urlread (\"http://www.google.com/search\", \"get\",\n\ @{\"query\", \"octave\"@});\n\ +@end group\n\ @end example\n\ @seealso{urlwrite}\n\ @end deftypefn")
--- a/src/bitfcns.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/bitfcns.cc Sat Mar 28 13:57:22 2009 -0700 @@ -415,6 +415,7 @@ @var{n} must be in the range [1,log2(bitmax)+1] usually [1,33]\n\ \n\ @example\n\ +@group\n\ bitshift (eye (3), 1)\n\ @result{}\n\ @group\n\ @@ -430,6 +431,7 @@ @c \n\ @c bitshift ([1, 10], 2, [3,4])\n\ @c @result{} 4 8\n\ +@end group\n\ @end example\n\ @seealso{bitand, bitor, bitxor, bitset, bitget, bitcmp, bitmax}\n\ @end deftypefn")
--- a/src/data.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/data.cc Sat Mar 28 13:57:22 2009 -0700 @@ -737,7 +737,7 @@ "-*- texinfo -*-\n\ @deftypefn {Mapping Function} {} hypot (@var{x}, @var{y})\n\ Compute square-root of the squares of @var{x} and @var{y}\n\ -element-by-element. This equivalent to @code{sqrt (@var{x}.^ 2 + @var{y}\n\ +element-by-element. This equivalent to @code{sqrt (@var{x}.^ 2 + @var{y}\n\ .^ 2)}, but calculated in a manner that avoids overflows for large\n\ values of @var{x} or @var{y}.\n\ @end deftypefn") @@ -992,11 +992,11 @@ DEFUN (log2, args, nargout, "-*- texinfo -*-\n\ @deftypefn {Mapping Function} {} log2 (@var{x})\n\ -@deftypefnx {Mapping Function} {[@var{f}, @var{e}] = } log2 (@var{x})\n\ +@deftypefnx {Mapping Function} {[@var{f}, @var{e}] =} log2 (@var{x})\n\ Compute the base-2 logarithm for each element of @var{x}.\n\ If called with two output arguments, split @var{x} to\n\ binary mantissa and exponent so that @code{1/2 <= abs(f) < 1} and\n\ -@var{e} is an integer. If @code{x = 0}, @code{f = e = 0}.\n\ +@var{e} is an integer. If @code{x = 0}, @code{f = e = 0}.\n\ @seealso{log, log10, log2, exp}\n\ @end deftypefn") { @@ -2263,7 +2263,7 @@ @deftypefn {Built-in Function} {} length (@var{a})\n\ Return the `length' of the object @var{a}. For matrix objects, the\n\ length is the number of rows or columns, whichever is greater (this\n\ -odd definition is used for compatibility with @sc{Matlab}).\n\ +odd definition is used for compatibility with @sc{matlab}).\n\ @end deftypefn") { octave_value retval; @@ -2356,8 +2356,10 @@ corresponding dimension. For example\n\ \n\ @example\n\ +@group\n\ size ([1, 2; 3, 4; 5, 6], 2)\n\ @result{} 2\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -2490,7 +2492,7 @@ @deftypefn {Built-in Function} {@var{scalar} =} nzmax (@var{SM})\n\ Return the amount of storage allocated to the sparse matrix @var{SM}.\n\ Note that Octave tends to crop unused memory at the first opportunity\n\ -for sparse objects. There are some cases of user created sparse objects\n\ +for sparse objects. There are some cases of user created sparse objects\n\ where the value returned by @dfn{nzmaz} will not be the same as @dfn{nnz},\n\ but in general they will give the same result.\n\ @seealso{sparse, spalloc}\n\ @@ -2552,13 +2554,15 @@ \n\ If the optional argument 'native' is given, then the sum is performed\n\ in the same type as the original argument, rather than in the default\n\ -double type. For example\n\ +double type. For example\n\ \n\ @example\n\ +@group\n\ sum ([true, true])\n\ @result{} 2\n\ sum ([true, true], 'native')\n\ @result{} true\n\ +@end group\n\ @end example\n\ @end deftypefn") { @@ -3802,7 +3806,7 @@ $1.1921\\times10^{-7}$.\n\ @end tex\n\ @end iftex\n\ -for single precision. Given a single argument @var{x}, return the\n\ +for single precision. Given a single argument @var{x}, return the\n\ distance between @var{x} and the next largest value.\n\ @end deftypefn") { @@ -4189,7 +4193,7 @@ \n\ Calling @code{eye} with no arguments is equivalent to calling it\n\ with an argument of 1. This odd definition is for compatibility\n\ -with @sc{Matlab}.\n\ +with @sc{matlab}.\n\ @end deftypefn") { octave_value retval; @@ -4273,7 +4277,7 @@ \n\ The @code{linspace} function always returns a row vector.\n\ \n\ -For compatibility with @sc{Matlab}, return the second argument if\n\ +For compatibility with @sc{matlab}, return the second argument if\n\ fewer than two values are requested.\n\ @end deftypefn") { @@ -4408,10 +4412,12 @@ is equivalent to the following code:\n\ \n\ @example\n\ +@group\n\ y = zeros (dv, class (x));\n\ sz = min (dv, size (x));\n\ for i = 1:length (sz), idx@{i@} = 1:sz(i); endfor\n\ y(idx@{:@}) = x(idx@{:@});\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -4635,7 +4641,7 @@ "-*- texinfo -*-\n\ @deftypefn {Built-in Function} {} squeeze (@var{x})\n\ Remove singleton dimensions from @var{x} and return the result.\n\ -Note that for compatibility with @sc{Matlab}, all objects have\n\ +Note that for compatibility with @sc{matlab}, all objects have\n\ a minimum of two dimensions and row vectors are left unchanged.\n\ @end deftypefn") { @@ -4719,7 +4725,7 @@ @end table\n\ \n\ If @code{\"rows\"} is given as @var{opt}, the norms of all rows of the matrix @var{a} are\n\ -returned as a column vector. Similarly, if @code{\"columns\"} or @code{\"cols\"} is passed\n\ +returned as a column vector. Similarly, if @code{\"columns\"} or @code{\"cols\"} is passed\n\ column norms are computed.\n\ @seealso{cond, svd}\n\ @end deftypefn") @@ -5129,9 +5135,11 @@ return the number of seconds since the timer was set. For example,\n\ \n\ @example\n\ +@group\n\ tic ();\n\ -# many computations later...\n\ +# many computations later@dots{}\n\ elapsed_time = toc ();\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -5687,7 +5695,7 @@ "-*- texinfo -*-\n\ @deftypefn {Function File} {} issorted (@var{a}, @var{rows})\n\ Returns true if the array is sorted, ascending or descending.\n\ -NaNs are treated is by @code{sort}. If @var{rows} is supplied and\n\ +NaNs are treated is by @code{sort}. If @var{rows} is supplied and\n\ has the value \"rows\", checks whether the array is sorted by rows\n\ as if output by @code{sortrows} (with no options).\n\ \n\
--- a/src/dirfns.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/dirfns.cc Sat Mar 28 13:57:22 2009 -0700 @@ -641,7 +641,7 @@ Return the system-dependent character used to separate directory names.\n\ \n\ If 'all' is given, the function return all valid file separators in\n\ -the form of a string. The list of file separators is system-dependent.\n\ +the form of a string. The list of file separators is system-dependent.\n\ It is / (forward slash) under UNIX or Mac OS X, / and \\ (forward and\n\ backward slashes) under Windows.\n\ @seealso{pathsep, dir, ls}\n\
--- a/src/graphics.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/graphics.cc Sat Mar 28 13:57:22 2009 -0700 @@ -5111,11 +5111,13 @@ Example:\n\ \n\ @example\n\ +@group\n\ function my_listener (h, dummy, p1)\n\ fprintf (\"my_listener called with p1=%s\\n\", p1);\n\ endfunction\n\ \n\ addlistener (gcf, \"position\", @{@@my_listener, \"my string\"@})\n\ +@end group\n\ @end example\n\ \n\ @end deftypefn") @@ -5172,6 +5174,7 @@ Example:\n\ \n\ @example\n\ +@group\n\ function my_listener (h, dummy, p1)\n\ fprintf (\"my_listener called with p1=%s\\n\", p1);\n\ endfunction\n\ @@ -5179,6 +5182,7 @@ c = @{@@my_listener, \"my string\"@};\n\ addlistener (gcf, \"position\", c);\n\ dellistener (gcf, \"position\", c);\n\ +@end group\n\ @end example\n\ \n\ @end deftypefn") @@ -5277,9 +5281,11 @@ Examples:\n\ \n\ @example\n\ +@group\n\ addproperty (\"my_property\", gcf, \"string\", \"a string value\");\n\ addproperty (\"my_radio\", gcf, \"radio\", \"val_1|val_2|@{val_3@}\");\n\ addproperty (\"my_style\", gcf, \"linelinestyle\", \"--\");\n\ +@end group\n\ @end example\n\ \n\ @end deftypefn")
--- a/src/help.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/help.cc Sat Mar 28 13:57:22 2009 -0700 @@ -245,8 +245,8 @@ pair_type ("case", "-*- texinfo -*-\n\ @deffn Keyword case @{@var{value}@}\n\ -A case statement in an switch. Octave cases are exclusive and do not\n\ -fall-through as do C-language cases. A switch statement must have at least\n\ +A case statement in an switch. Octave cases are exclusive and do not\n\ +fall-through as do C-language cases. A switch statement must have at least\n\ one case. See @code{switch} for an example.\n\ @seealso{switch}\n\ @end deffn"), @@ -268,7 +268,7 @@ pair_type ("do", "-*- texinfo -*-\n\ @deffn Keyword do\n\ -Begin a do-until loop. This differs from a do-while loop in that the\n\ +Begin a do-until loop. This differs from a do-while loop in that the\n\ body of the loop is executed at least once.\n\ @seealso{while}\n\ @end deffn"), @@ -348,17 +348,19 @@ @deffn Keyword for @var{i} = @var{range}\n\ Begin a for loop.\n\ @example\n\ +@group\n\ for i = 1:10\n\ i\n\ endfor\n\ +@end group\n\ @end example\n\ @seealso{do, while}\n\ @end deffn"), pair_type ("function", "-*- texinfo -*-\n\ -@deffn Keyword function @var{outputs} = function (@var{input}, ...)\n\ -@deffnx Keyword function {} function (@var{input}, ...)\n\ +@deffn Keyword function @var{outputs} = function (@var{input}, @dots{})\n\ +@deffnx Keyword function {} function (@var{input}, @dots{})\n\ @deffnx Keyword function @var{outputs} = function\n\ Begin a function body with @var{outputs} as results and @var{inputs} as\n\ parameters.\n\ @@ -370,10 +372,12 @@ @deffn Keyword global\n\ Declare variables to have global scope.\n\ @example\n\ +@group\n\ global @var{x};\n\ if isempty (@var{x})\n\ x = 1;\n\ endif\n\ +@end group\n\ @end example\n\ @seealso{persistent}\n\ @end deffn"), @@ -386,6 +390,7 @@ @deffnx Keyword if (@var{cond}) @dots{} elseif (@var{cond}) @dots{} else @dots{} endif\n\ Begin an if block.\n\ @example\n\ +@group\n\ x = 1;\n\ if (x == 1)\n\ disp (\"one\");\n\ @@ -394,6 +399,7 @@ else\n\ disp (\"not one or two\");\n\ endif\n\ +@end group\n\ @end example\n\ @seealso{switch}\n\ @end deffn"), @@ -442,6 +448,7 @@ @deffn Keyword switch @var{statement}\n\ Begin a switch block.\n\ @example\n\ +@group\n\ yesno = \"yes\"\n\ \n\ switch yesno\n\ @@ -452,6 +459,7 @@ otherwise\n\ error (\"invalid value\");\n\ endswitch\n\ +@end group\n\ @end example\n\ @seealso{if, case, otherwise}\n\ @end deffn"), @@ -732,7 +740,7 @@ Returns the help text of a given function.\n\ \n\ This function returns the raw help text @var{text} and an indication of\n\ -its format for the function @var{name}. The format indication @var{format}\n\ +its format for the function @var{name}. The format indication @var{format}\n\ is a string that can be either @t{\"texinfo\"}, @t{\"html\"}, or\n\ @t{\"plain text\"}.\n\ \n\
--- a/src/input.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/input.cc Sat Mar 28 13:57:22 2009 -0700 @@ -1390,8 +1390,8 @@ "-*- texinfo -*-\n\ @deftypefn {Built-in Function} {} filemarker ()\n\ Returns or sets the character used to separate filename from the\n\ -the subfunction names contained within the file. This can be used in\n\ -a generic manner to interact with subfunctions. For example\n\ +the subfunction names contained within the file. This can be used in\n\ +a generic manner to interact with subfunctions. For example\n\ \n\ @example\n\ help ([\"myfunc\", filemarker, \"mysubfunc\"])\n\ @@ -1399,7 +1399,7 @@ \n\ @noindent\n\ returns the help string associated with the sub-function @code{mysubfunc}\n\ -of the function @code{myfunc}. Another use of @code{filemarker} is when\n\ +of the function @code{myfunc}. Another use of @code{filemarker} is when\n\ debugging it allows easier placement of breakpoints within sub-functions.\n\ For example\n\ \n\
--- a/src/load-save.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/load-save.cc Sat Mar 28 13:57:22 2009 -0700 @@ -580,7 +580,7 @@ corresponding to the names of the variables in the file.\n\ \n\ The @code{load} command can read data stored in Octave's text and\n\ -binary formats, and @sc{Matlab}'s binary format. If compiled with zlib\n\ +binary formats, and @sc{matlab}'s binary format. If compiled with zlib\n\ support, it can load gzip-compressed files as well. It will automatically\n\ detect the type of file and do conversion from different floating point\n\ formats (currently only IEEE big and little endian, though other formats\n\ @@ -609,7 +609,7 @@ @itemx -v6\n\ @itemx -7\n\ @itemx -v7\n\ -Force Octave to assume the file is in @sc{Matlab}'s version 6 or 7 binary\n\ +Force Octave to assume the file is in @sc{matlab}'s version 6 or 7 binary\n\ format.\n\ \n\ @item -V4\n\ @@ -617,7 +617,7 @@ @itemx -4\n\ @itemx -mat4-binary\n\ Force Octave to assume the file is in the binary format written by\n\ -@sc{Matlab} version 4.\n\ +@sc{matlab} version 4.\n\ \n\ @item -hdf5\n\ Force Octave to assume the file is in HDF5 format.\n\ @@ -1480,7 +1480,7 @@ @itemx -v7\n\ @itemx -7\n\ @itemx -mat7-binary\n\ -Save the data in @sc{Matlab}'s v7 binary data format.\n" +Save the data in @sc{matlab}'s v7 binary data format.\n" HAVE_ZLIB_HELP_STRING @@ -1490,13 +1490,13 @@ @itemx -6\n\ @itemx -mat\n\ @itemx -mat-binary\n\ -Save the data in @sc{Matlab}'s v6 binary data format.\n\ +Save the data in @sc{matlab}'s v6 binary data format.\n\ \n\ @item -V4\n\ @itemx -v4\n\ @itemx -4\n\ @itemx -mat4-binary\n\ -Save the data in the binary format written by @sc{Matlab} version 4.\n\ +Save the data in the binary format written by @sc{matlab} version 4.\n\ \n\ @item -hdf5\n\ Save the data in HDF5 format.\n\ @@ -1534,7 +1534,7 @@ Match the list of characters specified by @var{list}. If the first\n\ character is @code{!} or @code{^}, match all characters except those\n\ specified by @var{list}. For example, the pattern @samp{[a-zA-Z]} will\n\ -match all lower and upper case alphabetic characters. \n\ +match all lower and upper case alphabetic characters. \n\ \n\ Wildcards may also be used in the field names specifications when using\n\ the @code{-struct} modifier (but not in the struct name itself).\n\ @@ -1543,7 +1543,7 @@ Save the data in Octave's text data format.\n\ @end table\n\ \n\ -Except when using the @sc{Matlab} binary data file format, saving global\n\ +Except when using the @sc{matlab} binary data file format, saving global\n\ variables also saves the global status of the variable, so that if it is\n\ restored at a later time using @samp{load}, it will be restored as a\n\ global variable.\n\
--- a/src/mappers.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/mappers.cc Sat Mar 28 13:57:22 2009 -0700 @@ -176,7 +176,7 @@ @deftypefnx {Mapping Function} {} angle (@var{z})\n\ Compute the argument of @var{z}, defined as\n\ @var{theta} = @code{atan2 (@var{y}, @var{x})}.\n\ -in radians. \n\ +in radians. \n\ \n\ For example,\n\ \n\ @@ -734,11 +734,13 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ infinity\n\ /\n\ gamma (z) = | t^(z-1) exp (-t) dt.\n\ /\n\ t=0\n\ +@end group\n\ @end example\n\ @end ifnottex\n\ @seealso{gammainc, lgamma}\n\ @@ -1301,8 +1303,8 @@ DEFUN (roundb, args, , "-*- texinfo -*-\n\ @deftypefn {Mapping Function} {} roundb (@var{x})\n\ -Return the integer nearest to @var{x}. If there are two nearest\n\ -integers, return the even one (banker's rounding). If @var{x} is complex,\n\ +Return the integer nearest to @var{x}. If there are two nearest\n\ +integers, return the even one (banker's rounding). If @var{x} is complex,\n\ return @code{roundb (real (@var{x})) + roundb (imag (@var{x})) * I}.\n\ @seealso{rem}\n\ @end deftypefn") @@ -1330,9 +1332,11 @@ @ifnottex\n\ \n\ @example\n\ +@group\n\ -1, x < 0;\n\ sign (x) = 0, x = 0;\n\ 1, x > 0.\n\ +@end group\n\ @end example\n\ @end ifnottex\n\ \n\ @@ -1568,8 +1572,10 @@ characters are left unchanged. For example,\n\ \n\ @example\n\ +@group\n\ tolower (\"MiXeD cAsE 123\")\n\ @result{} \"mixed case 123\"\n\ +@end group\n\ @end example\n\ @seealso{toupper}\n\ @end deftypefn") @@ -1607,7 +1613,7 @@ "-*- texinfo -*-\n\ @deftypefn {Built-in Function} {} toupper (@var{s})\n\ @deftypefnx {Built-in Function} {} upper (@var{s})\n\ -Return a copy of the string or cell string @var{s}, with each lower-case\n\ +Return a copy of the string or cell string @var{s}, with each lower-case\n\ character replaced by the corresponding upper-case one; nonalphabetic\n\ characters are left unchanged. For example,\n\ \n\
--- a/src/ov-base.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/ov-base.cc Sat Mar 28 13:57:22 2009 -0700 @@ -1397,6 +1397,7 @@ For example,\n\ \n\ @example\n\ +@group\n\ s = speye(3);\n\ sparse_auto_mutate (false)\n\ s (:, 1) = 1;\n\ @@ -1406,6 +1407,7 @@ s (1, :) = 1;\n\ typeinfo (s)\n\ @result{} matrix\n\ +@end group\n\ @end example\n\ @end deftypefn") {
--- a/src/ov-list.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/ov-list.cc Sat Mar 28 13:57:22 2009 -0700 @@ -398,9 +398,11 @@ elements are appended individually. For example,\n\ \n\ @example\n\ +@group\n\ x = list (1, 2);\n\ y = list (3, 4);\n\ append (x, y);\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\
--- a/src/ov.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/ov.cc Sat Mar 28 13:57:22 2009 -0700 @@ -2635,6 +2635,7 @@ a matrix\n\ \n\ @example\n\ +@group\n\ val = magic(3)\n\ @result{} val = [ 8 1 6\n\ 3 5 7\n\ @@ -2645,6 +2646,7 @@ @result{} [ 8 1 \n\ 3 5 \n\ 4 9 ]\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -2686,6 +2688,7 @@ 3-by-3 matrix to zero.\n\ \n\ @example\n\ +@group\n\ val = magic(3);\n\ idx.type = \"()\";\n\ idx.subs = @{\":\", 1:2@};\n\ @@ -2693,6 +2696,7 @@ @result{} [ 0 0 6\n\ 0 0 7\n\ 0 0 2 ]\n\ +@end group\n\ @end example\n\ \n\ Note that this is the same as writing @code{val(:,1:2) = 0}.\n\
--- a/src/pr-output.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/pr-output.cc Sat Mar 28 13:57:22 2009 -0700 @@ -3185,8 +3185,10 @@ You can convert the string back into a matrix as follows:\n\ \n\ @example\n\ +@group\n\ r = rats(hilb(4));\n\ x = str2num(r)\n\ +@end group\n\ @end example\n\ \n\ The optional second argument defines the maximum length of the string\n\ @@ -3264,10 +3266,12 @@ Display the value of @var{x}. For example,\n\ \n\ @example\n\ +@group\n\ disp (\"The value of pi is:\"), disp (pi)\n\ \n\ @print{} the value of pi is:\n\ @print{} 3.1416\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\ @@ -3306,10 +3310,12 @@ Display the value of @var{x} on the stream @var{fid}. For example,\n\ \n\ @example\n\ +@group\n\ fdisp (stdout, \"The value of pi is:\"), fdisp (stdout, pi)\n\ \n\ @print{} the value of pi is:\n\ @print{} 3.1416\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\
--- a/src/strfns.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/strfns.cc Sat Mar 28 13:57:22 2009 -0700 @@ -319,7 +319,7 @@ array of strings (of the same size or with only one element), char matrix\n\ or character string.\n\ \n\ -@strong{Caution:} For compatibility with @sc{Matlab}, Octave's strcmp\n\ +@strong{Caution:} For compatibility with @sc{matlab}, Octave's strcmp\n\ function returns 1 if the character strings are equal, and 0 otherwise.\n\ This is just the opposite of the corresponding C library function.\n\ @seealso{strcmpi, strncmp, strncmpi}\n\ @@ -633,7 +633,7 @@ @end group\n\ @end example\n\ \n\ -@strong{Caution:} For compatibility with @sc{Matlab}, Octave's strncmp\n\ +@strong{Caution:} For compatibility with @sc{matlab}, Octave's strncmp\n\ function returns 1 if the character strings are equal, and 0 otherwise.\n\ This is just the opposite of the corresponding C library function.\n\ @seealso{strncmpi, strcmp, strcmpi}\n\
--- a/src/syscalls.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/syscalls.cc Sat Mar 28 13:57:22 2009 -0700 @@ -725,7 +725,7 @@ DEFUN (fstat, args, , "-*- texinfo -*-\n\ @deftypefn {Built-in Function} {[@var{info}, @var{err}, @var{msg}] =} fstat (@var{fid})\n\ -Return information about about the open file @var{fid}. See @code{stat}\n\ +Return information about the open file @var{fid}. See @code{stat}\n\ for a description of the contents of @var{info}.\n\ @end deftypefn") { @@ -1463,7 +1463,7 @@ "-*- texinfo -*-\n\ @deftypefn {Built-in Function} {} WTERMSIG (@var{status})\n\ Given @var{status} from a call to @code{waitpid}, return the number of\n\ -the signal that caused the child process to terminate. This function\n\ +the signal that caused the child process to terminate. This function\n\ should only be employed if @code{WIFSIGNALED} returned true.\n\ @seealso{waitpid, WIFEXITED, WEXITSTATUS, WIFSIGNALED, WCOREDUMP, WIFSTOPPED, WSTOPSIG, WIFCONTINUED}\n\ @end deftypefn") @@ -1722,7 +1722,7 @@ @deftypefn {Built-in Function} {} O_APPEND ()\n\ Return the numerical value of the file status flag that may be\n\ returned by @code{fcntl} to indicate each write operation appends,\n\ -or that may be passed to @code{fcntl} to set the write mode to append.\ +or that may be passed to @code{fcntl} to set the write mode to append.\\n\ @seealso{fcntl, O_ASYNC, O_CREAT, O_EXCL, O_NONBLOCK, O_RDONLY, O_RDWR, O_SYNC, O_TRUNC, O_WRONLY}\n\ @end deftypefn") {
--- a/src/utils.cc Mon Mar 30 19:48:56 2009 -0400 +++ b/src/utils.cc Sat Mar 28 13:57:22 2009 -0700 @@ -342,8 +342,10 @@ is found, return an empty matrix. For example,\n\ \n\ @example\n\ +@group\n\ file_in_path (EXEC_PATH, \"sh\")\n\ @result{} \"/bin/sh\"\n\ +@end group\n\ @end example\n\ \n\ If the second argument is a cell array of strings, search each\n\ @@ -713,8 +715,10 @@ special characters replaced by their escape sequences. For example,\n\ \n\ @example\n\ +@group\n\ octave:13> undo_string_escapes (bell)\n\ ans = \\a\n\ +@end group\n\ @end example\n\ \n\ @noindent\n\