new file mode 100644
--- /dev/null
+++ b/scripts/general/interp1.m
@@ -0,0 +1,442 @@
+## Copyright (C) 2000 Paul Kienzle
+##
+## This file is part of Octave.
+##
+## Octave 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 2, or (at your option)
+## any later version.
+##
+## Octave 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 Octave; see the file COPYING.  If not, write to the Free
+## Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
+## 02110-1301, USA.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{yi} =} interp1 (@var{x}, @var{y}, @var{xi})
+## @deftypefnx {Function File} {@var{yi} =} interp1 (@dots{}, @var{method})
+## @deftypefnx {Function File} {@var{yi} =} interp1 (@dots{}, @var{extrap})
+## @deftypefnx {Function File} {@var{pp} =} interp1 (@dots{}, 'pp')
+##
+## One-dimensional interpolation. Interpolate @var{y}, defined at the
+## points @var{x}, at the points @var{xi}. The sample points @var{x} 
+## must be strictly monotonic. If @var{y} is an array, treat the columns
+## of @var{y} seperately.
+##
+## Method is one of:
+##
+## @table @asis
+## @item 'nearest'
+## Return the nearest neighbour.
+## @item 'linear'
+## Linear interpolation from nearest neighbours
+## @item 'pchip'
+## Piece-wise cubic hermite interpolating polynomial
+## @item 'cubic'
+## Cubic interpolation from four nearest neighbours
+## @item 'spline'
+## Cubic spline interpolation--smooth first and second derivatives
+## throughout the curve
+## @end table
+##
+## Appending '*' to the start of the above method forces @code{interp1}
+## to assume that @var{x} is uniformly spaced, and only @code{@var{x}
+## (1)} and @code{@var{x} (2)} are referenced. This is usually faster,
+## and is never slower. The default method is 'linear'.
+##
+## If @var{extrap} is the string 'extrap', then extrapolate values beyond
+## the endpoints.  If @var{extrap} is a number, replace values beyond the
+## endpoints with that number.  If @var{extrap} is missing, assume NaN.
+##
+## If the string argument 'pp' is specified, then @var{xi} should not be
+## supplied and @code{interp1} returns the piece-wise polynomial that
+## can later be used with @code{ppval} to evaluate the interpolation.
+## There is an equivalence, such that @code{ppval (interp1 (@var{x},
+## @var{y}, @var{method}, 'pp'), @var{xi}) == interp1 (@var{x}, @var{y},
+## @var{xi}, @var{method}, 'extrap')}.
+##
+## An example of the use of @code{interp1} is
+##
+## @example
+## @group
+##    xf=[0:0.05:10]; yf = sin(2*pi*xf/5);
+##    xp=[0:10];      yp = sin(2*pi*xp/5);
+##    lin=interp1(xp,yp,xf);
+##    spl=interp1(xp,yp,xf,'spline');
+##    cub=interp1(xp,yp,xf,'cubic');
+##    near=interp1(xp,yp,xf,'nearest');
+##    plot(xf,yf,';original;',xf,lin,';linear;',xf,spl,';spline;',...
+##         xf,cub,';cubic;',xf,near,';nearest;',xp,yp,'*;;');
+## @end group
+## @end example
+##
+## @seealso{interpft}
+## @end deftypefn
+
+## 2000-03-25 Paul Kienzle
+##    added 'nearest' as suggested by Kai Habel
+## 2000-07-17 Paul Kienzle
+##    added '*' methods and matrix y
+##    check for proper table lengths
+## 2002-01-23 Paul Kienzle
+##    fixed extrapolation
+
+function yi = interp1(x, y, varargin)
+
+  if ( nargin < 3 || nargin > 6)
+    print_usage ();
+  endif
+
+  method = "linear";
+  extrap = NaN;
+  xi = [];
+  pp = false;
+  firstnumeric = true;
+
+  if (nargin > 2)
+    for i = 1:length(varargin)
+      arg = varargin{i};
+      if (ischar(arg))
+	arg = tolower (arg);
+	if (strcmp("extrap",arg))
+	  extrap = "extrap";
+	elseif (strcmp("pp",arg))
+	  pp = true;
+	else
+	  method = arg;
+	endif
+      else
+	if (firstnumeric)
+	  xi = arg;
+	  firstnumeric = false;
+	else
+	  extrap = arg;
+	endif
+      endif
+    endfor
+  endif
+
+  ## reshape matrices for convenience
+  x = x(:);
+  nx = size(x,1);
+  if (isvector(y) && size (y, 1) == 1)
+    y = y (:);
+  endif
+  ndy = ndims (y);
+  szy = size(y);
+  ny = szy(1);
+  nc = prod (szy(2:end));
+  y = reshape (y, ny, nc);
+  szx = size(xi);
+  xi = xi(:);
+
+  ## determine sizes
+  if (nx < 2 || ny < 2)
+     error ("interp1: table too short");
+  endif
+
+  ## determine which values are out of range and set them to extrap,
+  ## unless extrap=="extrap" in which case, extrapolate them like we
+  ## should be doing in the first place.
+  minx = x(1);
+  if (method(1) == "*")
+     dx = x(2) - x(1);
+     maxx = minx + (ny-1)*dx;
+  else
+     maxx = x(nx);
+  endif
+  if (!pp)
+    if ischar(extrap) && strcmp(extrap,"extrap")
+      range=1:size(xi,1);
+      yi = zeros(size(xi,1), size(y,2));
+    else
+      range = find(xi >= minx & xi <= maxx);
+      yi = extrap*ones(size(xi,1), size(y,2));
+      if isempty(range), 
+	if (!isvector(y) && length(szx) == 2 && (szx(1) == 1 || szx(2) == 1))
+	  if (szx(1) == 1)
+	    yi = reshape (yi, [szx(2), szy(2:end)]);
+	  else
+	    yi = reshape (yi, [szx(1), szy(2:end)]);
+	  endif
+	else
+	  yi = reshape (yi, [szx, szy(2:end)]);
+        endif
+        return; 
+      endif
+      xi = xi(range);
+    endif
+  endif
+
+  if strcmp(method, "nearest")
+    if (pp)
+      yi = mkpp ([x(1);(x(1:end-1)+x(2:end))/2;x(end)],y,szy(2:end));
+    else
+      idx = lookup(0.5*(x(1:nx-1)+x(2:nx)), xi)+1;
+      yi(range,:) = y(idx,:);
+    endif
+  elseif strcmp(method, "*nearest")
+    if (pp)
+      yi = mkpp ([minx; minx + [0.5:(ny-1)]'*dx; maxx],y,szy(2:end));
+    else
+      idx = max(1,min(ny,floor((xi-minx)/dx+1.5)));
+      yi(range,:) = y(idx,:);
+    endif
+  elseif strcmp(method, "linear")
+    dy = y(2:ny,:) - y(1:ny-1,:);
+    dx = x(2:nx) - x(1:nx-1);
+    if (pp)
+      yi = mkpp(x, [dy./dx, y(1:end-1)],szy(2:end));
+    else
+      ## find the interval containing the test point
+      idx = lookup (x(2:nx-1), xi)+1; 
+				# 2:n-1 so that anything beyond the ends
+				# gets dumped into an interval
+      ## use the endpoints of the interval to define a line
+      s = (xi - x(idx))./dx(idx);
+      yi(range,:) = s(:,ones(1,nc)).*dy(idx,:) + y(idx,:);
+    endif
+  elseif strcmp(method, "*linear")
+    if (pp)
+      dy = [y(2:ny,:) - y(1:ny-1,:)];
+      yi = mkpp (minx + [0:ny-1]*dx, [dy ./ dx, y(1:end-1)], szy(2:end));
+    else
+      ## find the interval containing the test point
+      t = (xi - minx)/dx + 1;
+      idx = max(1,min(ny,floor(t)));
+
+      ## use the endpoints of the interval to define a line
+      dy = [y(2:ny,:) - y(1:ny-1,:); y(ny,:) - y(ny-1,:)];
+      s = t - idx;
+      yi(range,:) = s(:,ones(1,nc)).*dy(idx,:) + y(idx,:); 
+    endif
+  elseif strcmp(method, "pchip") || strcmp(method, "*pchip")
+    if (nx == 2 || method(1) == "*") 
+      x = linspace(minx, maxx, ny); 
+    endif
+    ## Note that pchip's arguments are transposed relative to interp1
+    if (pp)
+      yi = pchip(x.', y.');
+      yi.d = szy(2:end);
+    else
+      yi(range,:) = pchip(x.', y.', xi.').';
+    endif
+
+  elseif strcmp(method, "cubic") || (strcmp(method, "*cubic") && pp)
+    ## FIXME Is there a better way to treat pp return return and *cubic
+    if (method(1) == "*") 
+      x = linspace(minx, maxx, ny).'; 
+      nx = ny;
+    endif
+
+    if (nx < 4 || ny < 4)
+      error ("interp1: table too short");
+    endif
+    idx = lookup(x(3:nx-2), xi) + 1;
+
+    ## Construct cubic equations for each interval using divided
+    ## differences (computation of c and d don't use divided differences
+    ## but instead solve 2 equations for 2 unknowns). Perhaps
+    ## reformulating this as a lagrange polynomial would be more efficient.
+    i=1:nx-3;
+    J = ones(1,nc);
+    dx = diff(x);
+    dx2 = x(i+1).^2 - x(i).^2;
+    dx3 = x(i+1).^3 - x(i).^3;
+    a=diff(y,3)./dx(i,J).^3/6;
+    b=(diff(y(1:nx-1,:),2)./dx(i,J).^2 - 6*a.*x(i+1,J))/2;
+    c=(diff(y(1:nx-2,:),1) - a.*dx3(:,J) - b.*dx2(:,J))./dx(i,J);
+    d=y(i,:) - ((a.*x(i,J) + b).*x(i,J) + c).*x(i,J);
+
+    if (pp)
+      xs = [x(1);x(3:nx-2)];
+      yi = mkpp ([x(1);x(3:nx-2);x(nx)], 
+		 [a(:), (b(:) + 3.*xs(:,J).*a(:)), ... 
+		  (c(:) + 2.*xs(:,J).*b(:) + 3.*xs(:,J)(:).^2.*a(:)), ...
+		  (d(:) + xs(:,J).*c(:) + xs(:,J).^2.*b(:) + ...
+		   xs(:,J).^3.*a(:))], szy(2:end));
+    else
+      yi(range,:) = ((a(idx,:).*xi(:,J) + b(idx,:)).*xi(:,J) ...
+		     + c(idx,:)).*xi(:,J) + d(idx,:);
+    endif
+  elseif strcmp(method, "*cubic")
+    if (nx < 4 || ny < 4)
+      error ("interp1: table too short");
+    endif
+
+    ## From: Miloje Makivic 
+    ## http://www.npac.syr.edu/projects/nasa/MILOJE/final/node36.html
+    t = (xi - minx)/dx + 1;
+    idx = max(min(floor(t), ny-2), 2);
+    t = t - idx;
+    t2 = t.*t;
+    tp = 1 - 0.5*t;
+    a = (1 - t2).*tp;
+    b = (t2 + t).*tp;
+    c = (t2 - t).*tp/3;
+    d = (t2 - 1).*t/6;
+    J = ones(1,nc);
+
+    yi(range,:) = a(:,J) .* y(idx,:) + b(:,J) .* y(idx+1,:) ...
+		  + c(:,J) .* y(idx-1,:) + d(:,J) .* y(idx+2,:);
+
+  elseif strcmp(method, "spline") || strcmp(method, "*spline")
+    if (nx == 2 || method(1) == "*") 
+      x = linspace(minx, maxx, ny); 
+    endif
+    ## Note that spline's arguments are transposed relative to interp1
+    if (pp)
+      yi = spline(x.', y.');
+      yi.d = szy(2:end);
+    else
+      yi(range,:) = spline(x.', y.', xi.').';
+    endif
+  else
+    error(["interp1 doesn't understand method '", method, "'"]);
+  endif
+
+  if (!pp)
+    if (!isvector(y) && length(szx) == 2 && (szx(1) == 1 || szx(2) == 1))
+      if (szx(1) == 1)
+	yi = reshape (yi, [szx(2), szy(2:end)]);
+      else
+	yi = reshape (yi, [szx(1), szy(2:end)]);
+      endif
+    else
+      yi = reshape (yi, [szx, szy(2:end)]);
+    endif
+  endif
+
+endfunction
+
+%!demo
+%! xf=0:0.05:10; yf = sin(2*pi*xf/5);
+%! xp=0:10;      yp = sin(2*pi*xp/5);
+%! lin=interp1(xp,yp,xf,"linear");
+%! spl=interp1(xp,yp,xf,"spline");
+%! cub=interp1(xp,yp,xf,"pchip");
+%! near=interp1(xp,yp,xf,"nearest");
+%! plot(xf,yf,";original;",xf,near,";nearest;",xf,lin,";linear;",...
+%!      xf,cub,";pchip;",xf,spl,";spline;",xp,yp,"*;;");
+%! %--------------------------------------------------------
+%! % confirm that interpolated function matches the original
+
+%!demo
+%! xf=0:0.05:10; yf = sin(2*pi*xf/5);
+%! xp=0:10;      yp = sin(2*pi*xp/5);
+%! lin=interp1(xp,yp,xf,"*linear");
+%! spl=interp1(xp,yp,xf,"*spline");
+%! cub=interp1(xp,yp,xf,"*cubic");
+%! near=interp1(xp,yp,xf,"*nearest");
+%! plot(xf,yf,";*original;",xf,near,";*nearest;",xf,lin,";*linear;",...
+%!      xf,cub,";*cubic;",xf,spl,";*spline;",xp,yp,"*;;");
+%! %--------------------------------------------------------
+%! % confirm that interpolated function matches the original
+
+%!shared xp, yp, xi, style
+%! xp=0:5;      yp = sin(2*pi*xp/5);
+%! xi = sort([-1, max(xp)*rand(1,6), max(xp)+1]);
+
+%!test style = "nearest";
+%!assert (interp1(xp, yp, [min(xp)-1, max(xp)+1]), [NaN, NaN]);
+%!assert (interp1(xp,yp,xp,style), yp, 100*eps);
+%!assert (interp1(xp,yp,xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp,style), yp, 100*eps);
+%!assert (isempty(interp1(xp',yp',[],style)));
+%!assert (isempty(interp1(xp,yp,[],style)));
+%!assert (interp1(xp,[yp',yp'],xi(:),style),...
+%!	  [interp1(xp,yp,xi(:),style),interp1(xp,yp,xi(:),style)]);
+%!assert (interp1(xp,[yp',yp'],xi,style),
+%!	  interp1(xp,[yp',yp'],xi,["*",style]));
+
+%!test style = "linear";
+%!assert (interp1(xp, yp, [-1, max(xp)+1]), [NaN, NaN]);
+%!assert (interp1(xp,yp,xp,style), yp, 100*eps);
+%!assert (interp1(xp,yp,xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp,style), yp, 100*eps);
+%!assert (isempty(interp1(xp',yp',[],style)));
+%!assert (isempty(interp1(xp,yp,[],style)));
+%!assert (interp1(xp,[yp',yp'],xi(:),style),...
+%!	  [interp1(xp,yp,xi(:),style),interp1(xp,yp,xi(:),style)]);
+%!assert (interp1(xp,[yp',yp'],xi,style),
+%!	  interp1(xp,[yp',yp'],xi,["*",style]),100*eps);
+
+%!test style = "cubic";
+%!assert (interp1(xp, yp, [-1, max(xp)+1]), [NaN, NaN]);
+%!assert (interp1(xp,yp,xp,style), yp, 100*eps);
+%!assert (interp1(xp,yp,xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp,style), yp, 100*eps);
+%!assert (isempty(interp1(xp',yp',[],style)));
+%!assert (isempty(interp1(xp,yp,[],style)));
+%!assert (interp1(xp,[yp',yp'],xi(:),style),...
+%!	  [interp1(xp,yp,xi(:),style),interp1(xp,yp,xi(:),style)]);
+%!assert (interp1(xp,[yp',yp'],xi,style),
+%!	  interp1(xp,[yp',yp'],xi,["*",style]),1000*eps);
+
+%!test style = "spline";
+%!assert (interp1(xp, yp, [-1, max(xp) + 1]), [NaN, NaN]);
+%!assert (interp1(xp,yp,xp,style), yp, 100*eps);
+%!assert (interp1(xp,yp,xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp',style), yp', 100*eps);
+%!assert (interp1(xp',yp',xp,style), yp, 100*eps);
+%!assert (isempty(interp1(xp',yp',[],style)));
+%!assert (isempty(interp1(xp,yp,[],style)));
+%!assert (interp1(xp,[yp',yp'],xi(:),style),...
+%!	  [interp1(xp,yp,xi(:),style),interp1(xp,yp,xi(:),style)]);
+%!assert (interp1(xp,[yp',yp'],xi,style),
+%!	  interp1(xp,[yp',yp'],xi,["*",style]),10*eps);
+
+%!# test linear extrapolation
+%!assert (interp1([1:5],[3:2:11],[0,6],"linear","extrap"), [1, 13], eps);
+%!assert (interp1(xp, yp, [-1, max(xp)+1],"linear",5), [5, 5]);
+
+%!error interp1
+%!error interp1(1:2,1:2,1,"bogus")
+
+%!error interp1(1,1,1, "nearest");
+%!assert (interp1(1:2,1:2,1.4,"nearest"),1);
+%!error interp1(1,1,1, "linear");
+%!assert (interp1(1:2,1:2,1.4,"linear"),1.4);
+%!error interp1(1:3,1:3,1, "cubic");
+%!assert (interp1(1:4,1:4,1.4,"cubic"),1.4);
+%!error interp1(1:2,1:2,1, "spline");
+%!assert (interp1(1:3,1:3,1.4,"spline"),1.4);
+
+%!error interp1(1,1,1, "*nearest");
+%!assert (interp1(1:2:4,1:2:4,1.4,"*nearest"),1);
+%!error interp1(1,1,1, "*linear");
+%!assert (interp1(1:2:4,1:2:4,[0,1,1.4,3,4],"*linear"),[NaN,1,1.4,3,NaN]);
+%!error interp1(1:3,1:3,1, "*cubic");
+%!assert (interp1(1:2:8,1:2:8,1.4,"*cubic"),1.4);
+%!error interp1(1:2,1:2,1, "*spline");
+%!assert (interp1(1:2:6,1:2:6,1.4,"*spline"),1.4);
+
+%!assert (ppval(interp1(xp,yp,"nearest","pp"),xi),
+%!	  interp1(xp,yp,xi,"nearest","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"linear","pp"),xi),
+%!	  interp1(xp,yp,xi,"linear","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"cubic","pp"),xi),
+%!	  interp1(xp,yp,xi,"cubic","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"pchip","pp"),xi),
+%!	  interp1(xp,yp,xi,"pchip","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"spline","pp"),xi),
+%!	  interp1(xp,yp,xi,"spline","extrap"),10*eps);
+
+%!assert (ppval(interp1(xp,yp,"*nearest","pp"),xi),
+%!	  interp1(xp,yp,xi,"*nearest","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"*linear","pp"),xi),
+%!	  interp1(xp,yp,xi,"*linear","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"*cubic","pp"),xi),
+%!	  interp1(xp,yp,xi,"*cubic","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"*pchip","pp"),xi),
+%!	  interp1(xp,yp,xi,"*pchip","extrap"),10*eps);
+%!assert (ppval(interp1(xp,yp,"*spline","pp"),xi),
+%!	  interp1(xp,yp,xi,"*spline","extrap"),10*eps);