Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / data-smoothing-1.3.0 / rgdtsmcorewrap.m

diff --git a/octave_packages/data-smoothing-1.3.0/rgdtsmcorewrap.m b/octave_packages/data-smoothing-1.3.0/rgdtsmcorewrap.m
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+## Copyright (C) 2008 Jonathan Stickel <jonathan.stickel@nrel.gov>
+##
+## This program is free software; you can redistribute it and/or modify it under
+## the terms of the GNU General Public License as published by the Free Software
+## Foundation; either version 3 of the License, or (at your option) any later
+## version.
+##
+## This program is distributed in the hope that it will be useful, but WITHOUT
+## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
+## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
+## details.
+##
+## You should have received a copy of the GNU General Public License along with
+## this program; if not, see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{cve} =} rgdtsmcorewrap (@var{log10lambda}, @var{x}, @var{y}, @var{d}, @var{mincell}, @var{options})
+## @deftypefnx {Function File} {@var{stdevdif} =} rgdtsmcorewrap (@var{log10lambda}, @var{x}, @var{y}, @var{d}, @var{mincell}, @var{options})
+##
+##  Wrapper function for rgdtsmcore in order to minimize over
+##  @var{lambda} w.r.t. cross-validation error OR the squared difference
+##  between the standard deviation of (@var{y}-@var{yhat}) and the given
+##  standard deviation.  This function is called from regdatasmooth.
+## @seealso{regdatasmooth}
+## @end deftypefn
+
+function out = rgdtsmcorewrap (log10lambda, x, y, d, mincell, varargin)
+
+  if (nargin < 5)
+    print_usage;
+  endif
+
+  lambda = 10^(log10lambda);
+
+  if ( length(mincell) == 2 ) # using stdev to find optimal lambda
+    stdev = mincell{2};
+    yhat  = rgdtsmcore (x, y, d, lambda, varargin{:});
+
+    xhatprov = 0;
+    relative = 0;
+    for i = 1:length(varargin)
+      if strcmp(varargin{i},"relative")
+        relative = 1;
+      elseif strcmp(varargin{i},"xhat")
+        xhatprov = 1;
+        xhat = varargin{i+1};
+      endif
+    endfor
+
+    if (xhatprov)
+      idx = interp1(xhat,1:length(xhat),x,"nearest");
+      if relative
+        stdevd = std((y-yhat(idx))./y);
+      else
+        stdevd = std(y-yhat(idx));
+      endif
+    else
+      if (relative)
+        stdevd = std((y-yhat)./y);
+      else
+        stdevd = std(y-yhat);
+      endif
+    endif
+
+    out = (stdevd - stdev)^2;
+
+  else # use gcv to find optimal lambda
+    [yhat, out] = rgdtsmcore (x, y, d, lambda, varargin{:});
+  endif
+
+endfunction