octave-nkf: src/data.cc comparison

comparison src/data.cc @ 8303:b11c31849b44

improve norm computation capabilities

author	Jaroslav Hajek <highegg@gmail.com>
date	Fri, 31 Oct 2008 08:05:32 +0100
parents	6f2d95255911
children	fa78cb8d8a5c

comparison

equal deleted inserted replaced

-:f2e050b62199
+:b11c31849b44
 #include "parse.h"
 #include "pt-mat.h"
 #include "utils.h"
 #include "variables.h"
 #include "pager.h"
+#include "xnorm.h"
 #if ! defined (HAVE_HYPOTF) && defined (HAVE__HYPOTF)
 #define hypotf _hypotf
 #define HAVE_HYPOTF 1
 #endif
 // Compute various norms of the vector X.
 DEFUN (norm, args, ,
 "-*- texinfo -*-\n\
-@deftypefn {Function File} {} norm (@var{a}, @var{p})\n\
+@deftypefn {Function File} {} norm (@var{a}, @var{p}, @var{opt})\n\
 Compute the p-norm of the matrix @var{a}.  If the second argument is\n\
 missing, @code{p = 2} is assumed.\n\
 \n\
-If @var{a} is a matrix:\n\
+If @var{a} is a matrix (or sparse matrix):\n\
 \n\
 @table @asis\n\
 @item @var{p} = @code{1}\n\
 1-norm, the largest column sum of the absolute values of @var{a}.\n\
 \n\
 Infinity norm, the largest row sum of the absolute values of @var{a}.\n\
 \n\
 @item @var{p} = @code{\"fro\"}\n\
 @cindex Frobenius norm\n\
 Frobenius norm of @var{a}, @code{sqrt (sum (diag (@var{a}' * @var{a})))}.\n\
+\n\
+@item other @var{p}, @code{@var{p} > 1}\n\
+@cindex general p-norm \n\
+maximum @code{norm (A*x, p)} such that @code{norm (x, p) == 1}\n\
 @end table\n\
 \n\
 If @var{a} is a vector or a scalar:\n\
 \n\
 @table @asis\n\
 @code{min (abs (@var{a}))}.\n\
 \n\
 @item @var{p} = @code{\"fro\"}\n\
 Frobenius norm of @var{a}, @code{sqrt (sumsq (abs (a)))}.\n\
 \n\
-@item other\n\
+@item @var{p} = 0\n\
+Hamming norm - the number of nonzero elements.\n\
+\n\
+@item other @var{p}, @code{@var{p} > 1}\n\
 p-norm of @var{a}, @code{(sum (abs (@var{a}) .^ @var{p})) ^ (1/@var{p})}.\n\
+\n\
+@item other @var{p} @code{@var{p} < 1}\n\
+the p-pseudonorm defined as above.\n\
 @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\
+column norms are computed.\n\
 @seealso{cond, svd}\n\
 @end deftypefn")
 {
-// Currently only handles vector norms for full double/complex
-// vectors internally.  Other cases are handled by __norm__.m.
 octave_value_list retval;
 int nargin = args.length ();
-if (nargin == 1 || nargin == 2)
+if (nargin >= 1 && nargin <= 3)
 {
 octave_value x_arg = args(0);
 if (x_arg.is_empty ())
 	{
 	  else
 	    retval(0) = 0.0;
 	}
 else if (x_arg.ndims () == 2)
 	{
-	  if ((x_arg.rows () == 1 || x_arg.columns () == 1)
+enum { sfmatrix, sfcols, sfrows, sffrob, sfinf } strflag = sfmatrix;
-	      && ! (x_arg.is_sparse_type () || x_arg.is_integer_type ()))
+if (nargin > 1 && args(nargin-1).is_string ())
-	    {
+{
-	      double p_val = 2;
+std::string str = args(nargin-1).string_value ();
+if (str == "cols" || str == "columns")
-	      if (nargin == 2)
+strflag = sfcols;
-		{
+else if (str == "rows")
-		  octave_value p_arg = args(1);
+strflag = sfrows;
+else if (str == "fro")
-		  if (p_arg.is_string ())
+strflag = sffrob;
-		    {
+else if (str == "inf")
-		      std::string p = args(1).string_value ();
+strflag = sfinf;
+else
-		      if (p == "inf")
+error ("norm: unrecognized option: %s", str.c_str ());
-			p_val = octave_Inf;
+// we've handled the last parameter, so act as if it was removed
-		      else if (p == "fro")
+nargin --;
-			p_val = -1;
+}
-		      else
+else if (nargin > 1 && ! args(1).is_scalar_type ())
-			error ("norm: unrecognized norm `%s'", p.c_str ());
+gripe_wrong_type_arg ("norm", args(1), true);
-		    }
-		  else
+if (! error_state)
-		    {
+{
-		      p_val = p_arg.double_value ();
+octave_value p_arg = (nargin > 1) ? args(1) : octave_value (2);
+switch (strflag)
-		      if (error_state)
+{
-			error ("norm: unrecognized norm value");
+case sfmatrix:
-		    }
+retval(0) = xnorm (x_arg, p_arg);
-		}
+break;
+case sfcols:
-	      if (x_arg.is_single_type ())
+retval(0) = xcolnorms (x_arg, p_arg);
-		{
+break;
-		  if (! error_state)
+case sfrows:
-		    {
+retval(0) = xrownorms (x_arg, p_arg);
-		      if (x_arg.is_real_type ())
+break;
-			{
+case sffrob:
-			  MArray<float> x (x_arg.float_array_value ());
+retval(0) = xfrobnorm (x_arg);
+break;
-			  if (! error_state)
+case sfinf:
-			    retval(0) = x.norm (static_cast<float>(p_val));
+retval(0) = xnorm (x_arg, octave_Inf);
-			  else
+break;
-			    error ("norm: expecting real vector");
+}
-			}
+}
-		      else
-			{
-			  MArray<FloatComplex> x (x_arg.float_complex_array_value ());
-			  if (! error_state)
-			    retval(0) = x.norm (static_cast<float>(p_val));
-			  else
-			    error ("norm: expecting complex vector");
-			}
-		    }
-		}
-	      else
-		{
-		  if (! error_state)
-		    {
-		      if (x_arg.is_real_type ())
-			{
-			  MArray<double> x (x_arg.array_value ());
-			  if (! error_state)
-			    retval(0) = x.norm (p_val);
-			  else
-			    error ("norm: expecting real vector");
-			}
-		      else
-			{
-			  MArray<Complex> x (x_arg.complex_array_value ());
-			  if (! error_state)
-			    retval(0) = x.norm (p_val);
-			  else
-			    error ("norm: expecting complex vector");
-			}
-		    }
-		}
-	    }
-	  else
-	    retval = feval ("__norm__", args);
 	}
 else
 	error ("norm: only valid for 2-D objects");
 }
 else
 print_usage ();
-// Should not return a sparse type
-if (retval(0).is_sparse_type ())
-{
-if (retval(0).type_name () == "sparse matrix")
-	retval(0) = retval(0).matrix_value ();
-else if (retval(0).type_name () == "sparse complex matrix")
-	retval(0) = retval(0).complex_matrix_value ();
-else if (retval(0).type_name () == "sparse bool matrix")
-	retval(0) = retval(0).bool_matrix_value ();
-}
 return retval;
 }
 /*

Mercurial > octave-nkf

comparison src/data.cc @ 8303:b11c31849b44