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author | Stefan Mahr <dac922@gmx.de> |
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date | Fri, 27 Feb 2015 16:59:36 +0100 |
parents | 9fc020886ae9 |
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## Copyright (C) 2000-2015 Kai Habel ## Copyright (C) 2009 Jaroslav Hajek ## ## 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 3 of the License, 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, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {@var{zi} =} interp2 (@var{x}, @var{y}, @var{z}, @var{xi}, @var{yi}) ## @deftypefnx {Function File} {@var{zi} =} interp2 (@var{z}, @var{xi}, @var{yi}) ## @deftypefnx {Function File} {@var{zi} =} interp2 (@var{z}, @var{n}) ## @deftypefnx {Function File} {@var{zi} =} interp2 (@var{z}) ## @deftypefnx {Function File} {@var{zi} =} interp2 (@dots{}, @var{method}) ## @deftypefnx {Function File} {@var{zi} =} interp2 (@dots{}, @var{method}, @var{extrap}) ## ## Two-dimensional interpolation. ## ## Interpolate reference data @var{x}, @var{y}, @var{z} to determine @var{zi} ## at the coordinates @var{xi}, @var{yi}. The reference data @var{x}, @var{y} ## can be matrices, as returned by @code{meshgrid}, in which case the sizes of ## @var{x}, @var{y}, and @var{z} must be equal. If @var{x}, @var{y} are ## vectors describing a grid then @code{length (@var{x}) == columns (@var{z})} ## and @code{length (@var{y}) == rows (@var{z})}. In either case the input ## data must be strictly monotonic. ## ## If called without @var{x}, @var{y}, and just a single reference data matrix ## @var{z}, the 2-D region ## @code{@var{x} = 1:columns (@var{z}), @var{y} = 1:rows (@var{z})} is assumed. ## This saves memory if the grid is regular and the distance between points is ## not important. ## ## If called with a single reference data matrix @var{z} and a refinement ## value @var{n}, then perform interpolation over a grid where each original ## interval has been recursively subdivided @var{n} times. This results in ## @code{2^@var{n}-1} additional points for every interval in the original ## grid. If @var{n} is omitted a value of 1 is used. As an example, the ## interval [0,1] with @code{@var{n}==2} results in a refined interval with ## points at [0, 1/4, 1/2, 3/4, 1]. ## ## The interpolation @var{method} is one of: ## ## @table @asis ## @item @qcode{"nearest"} ## Return the nearest neighbor. ## ## @item @qcode{"linear"} (default) ## Linear interpolation from nearest neighbors. ## ## @item @qcode{"pchip"} ## Piecewise cubic Hermite interpolating polynomial---shape-preserving ## interpolation with smooth first derivative. ## ## @item @qcode{"cubic"} ## Cubic interpolation (same as @qcode{"pchip"}). ## ## @item @qcode{"spline"} ## Cubic spline interpolation---smooth first and second derivatives ## throughout the curve. ## @end table ## ## @var{extrap} is a scalar number. It replaces values beyond the endpoints ## with @var{extrap}. Note that if @var{extrapval} is used, @var{method} must ## be specified as well. If @var{extrap} is omitted and the @var{method} is ## @qcode{"spline"}, then the extrapolated values of the @qcode{"spline"} are ## used. Otherwise the default @var{extrap} value for any other @var{method} ## is @qcode{"NA"}. ## @seealso{interp1, interp3, interpn, meshgrid} ## @end deftypefn function ZI = interp2 (varargin) narginchk (1, 7); nargs = nargin; Z = X = Y = XI = YI = n = []; method = "linear"; extrap = []; ## Check for method and extrap if (nargs > 1 && ischar (varargin{end-1})) if (! isnumeric (varargin{end}) || ! isscalar (varargin{end})) error ("interp2: EXTRAP must be a numeric scalar"); endif extrap = varargin{end}; method = varargin{end-1}; nargs -= 2; elseif (ischar (varargin{end})) method = varargin{end}; nargs--; endif if (method(1) == "*") warning ("interp2: ignoring unsupported '*' flag to METHOD"); method(1) = []; endif method = validatestring (method, ... {"nearest", "linear", "pchip", "cubic", "spline"}); ## Read numeric input switch (nargs) case 1 Z = varargin{1}; n = 1; case 2 [Z, n] = deal (varargin{1:nargs}); case 3 [Z, XI, YI] = deal (varargin{1:nargs}); case 5 [X, Y, Z, XI, YI] = deal (varargin{1:nargs}); otherwise print_usage (); endswitch ## Type checking if (! isnumeric (Z) || isscalar (Z) || ! ismatrix (Z) || ndims (Z) != 2) error ("interp2: Z must be a 2-D matrix"); endif if (! isempty (n) && ! (isscalar (n) && n >= 0 && n == fix (n))) error ("interp2: N must be an integer >= 0"); endif ## Define X, Y, XI, YI if needed [zr, zc] = size (Z); if (isempty (X)) X = 1:zc; Y = 1:zr; endif if (! isnumeric (X) || ! isnumeric (Y)) error ("interp2: X, Y must be numeric matrices"); endif if (! isempty (n)) ## Calculate the interleaved input vectors. p = 2^n; XI = (p:p*zc)/p; YI = (p:p*zr)'/p; endif if (! isnumeric (XI) || ! isnumeric (YI)) error ("interp2: XI, YI must be numeric"); endif if (isvector (X) && isvector (Y)) X = X(:); Y = Y(:); elseif (size_equal (X, Y)) X = X(1,:).'; Y = Y(:,1); else error ("interp2: X and Y must be matrices of equal size"); endif if (columns (Z) != length (X) || rows (Z) != length (Y)) error ("interp2: X and Y size must match the dimensions of Z"); endif dx = diff (X); if (all (dx < 0)) X = flipud (X); Z = fliplr (Z); elseif (any (dx <= 0)) error ("interp2: X must be strictly monotonic"); endif dy = diff (Y); if (all (dy < 0)) Y = flipud (Y); Z = flipud (Z); elseif (any (dy <= 0)) error ("interp2: Y must be strictly monotonic"); endif if (any (strcmp (method, {"nearest", "linear", "pchip", "cubic"}))) ## If Xi and Yi are vectors of different orientation build a grid if ((rows (XI) == 1 && columns (YI) == 1) || (columns (XI) == 1 && rows (YI) == 1)) [XI, YI] = meshgrid (XI, YI); elseif (! size_equal (XI, YI)) error ("interp2: XI and YI must be matrices of equal size"); endif ## if XI, YI are vectors, X and Y should share their orientation. if (rows (XI) == 1) if (rows (X) != 1) X = X.'; endif if (rows (Y) != 1) Y = Y.'; endif elseif (columns (XI) == 1) if (columns (X) != 1) X = X.'; endif if (columns (Y) != 1) Y = Y.'; endif endif xidx = lookup (X, XI, "lr"); yidx = lookup (Y, YI, "lr"); if (strcmp (method, "linear")) ## each quad satisfies the equation z(x,y)=a+b*x+c*y+d*xy ## ## a-b ## | | ## c-d a = Z(1:(zr - 1), 1:(zc - 1)); b = Z(1:(zr - 1), 2:zc) - a; c = Z(2:zr, 1:(zc - 1)) - a; d = Z(2:zr, 2:zc) - a - b - c; ## scale XI, YI values to a 1-spaced grid Xsc = (XI - X(xidx)) ./ (diff (X)(xidx)); Ysc = (YI - Y(yidx)) ./ (diff (Y)(yidx)); ## Get 2D index. idx = sub2ind (size (a), yidx, xidx); ## We can dispose of the 1D indices at this point to save memory. clear xidx yidx; ## apply plane equation ZI = a(idx) + b(idx).*Xsc + c(idx).*Ysc + d(idx).*Xsc.*Ysc; elseif (strcmp (method, "nearest")) ii = (XI - X(xidx) >= X(xidx + 1) - XI); jj = (YI - Y(yidx) >= Y(yidx + 1) - YI); idx = sub2ind (size (Z), yidx+jj, xidx+ii); ZI = Z(idx); elseif (strcmp (method, "pchip") || strcmp (method, "cubic")) if (length (X) < 2 || length (Y) < 2) error ("interp2: %s requires at least 2 points in each dimension", method); endif ## first order derivatives DX = __pchip_deriv__ (X, Z, 2); DY = __pchip_deriv__ (Y, Z, 1); ## Compute mixed derivatives row-wise and column-wise, use the average. DXY = (__pchip_deriv__ (X, DY, 2) + __pchip_deriv__ (Y, DX, 1))/2; ## do the bicubic interpolation hx = diff (X); hx = hx(xidx); hy = diff (Y); hy = hy(yidx); tx = (XI - X(xidx)) ./ hx; ty = (YI - Y(yidx)) ./ hy; ## construct the cubic hermite base functions in x, y ## formulas: ## b{1,1} = ( 2*t.^3 - 3*t.^2 + 1); ## b{2,1} = h.*( t.^3 - 2*t.^2 + t ); ## b{1,2} = (-2*t.^3 + 3*t.^2 ); ## b{2,2} = h.*( t.^3 - t.^2 ); ## optimized equivalents of the above: t1 = tx.^2; t2 = tx.*t1 - t1; xb{2,2} = hx.*t2; t1 = t2 - t1; xb{2,1} = hx.*(t1 + tx); t2 += t1; xb{1,2} = -t2; xb{1,1} = t2 + 1; t1 = ty.^2; t2 = ty.*t1 - t1; yb{2,2} = hy.*t2; t1 = t2 - t1; yb{2,1} = hy.*(t1 + ty); t2 += t1; yb{1,2} = -t2; yb{1,1} = t2 + 1; ZI = zeros (size (XI)); for i = 1:2 for j = 1:2 zidx = sub2ind (size (Z), yidx+(j-1), xidx+(i-1)); ZI += xb{1,i} .* yb{1,j} .* Z(zidx); ZI += xb{2,i} .* yb{1,j} .* DX(zidx); ZI += xb{1,i} .* yb{2,j} .* DY(zidx); ZI += xb{2,i} .* yb{2,j} .* DXY(zidx); endfor endfor endif else ## Check dimensions of XI and YI if (isvector (XI) && isvector (YI) && ! size_equal (XI, YI)) XI = XI(:).'; YI = YI(:); elseif (! size_equal (XI, YI)) error ("interp2: XI and YI must be matrices of equal size"); endif if (strcmp (method, "spline")) if (isgriddata (XI) && isgriddata (YI')) ZI = __splinen__ ({Y, X}, Z, {YI(:,1), XI(1,:)}, extrap, "spline"); else error ("interp2: XI, YI must have uniform spacing ('meshgrid' format)"); endif endif return; # spline doesn't need NA extrapolation value (MATLAB compatibility) endif ## extrapolation 'extrap' if (isempty (extrap)) extrap = NA; endif if (X(1) < X(end)) if (Y(1) < Y(end)) ZI(XI < X(1,1) | XI > X(end) | YI < Y(1,1) | YI > Y(end)) = extrap; else ZI(XI < X(1) | XI > X(end) | YI < Y(end) | YI > Y(1)) = extrap; endif else if (Y(1) < Y(end)) ZI(XI < X(end) | XI > X(1) | YI < Y(1) | YI > Y(end)) = extrap; else ZI(XI < X(1,end) | XI > X(1) | YI < Y(end) | YI > Y(1)) = extrap; endif endif endfunction function b = isgriddata (X) d1 = diff (X, 1, 1); b = all (d1(:) == 0); endfunction ## Compute the bicubic interpolation coefficients function o = bc (x) x = abs (x); o = zeros (size (x)); idx1 = (x < 1); idx2 = !idx1 & (x < 2); o(idx1) = 1 - 2.*x(idx1).^2 + x(idx1).^3; o(idx2) = 4 - 8.*x(idx2) + 5.*x(idx2).^2 - x(idx2).^3; endfunction ## This version of sub2ind behaves as if the data was symmetrically padded function ind = sym_sub2ind (sz, Y, X) Y(Y < 1) = 1 - Y(Y < 1); while (any (Y(:) > 2*sz(1))) Y(Y > 2*sz(1)) = round (Y(Y > 2*sz(1)) / 2); endwhile Y(Y > sz(1)) = 1 + 2*sz(1) - Y(Y > sz(1)); X(X < 1) = 1 - X(X < 1); while (any (X(:) > 2*sz(2))) X(X > 2 * sz(2)) = round (X(X > 2*sz(2)) / 2); endwhile X(X > sz(2)) = 1 + 2*sz(2) - X(X > sz(2)); ind = sub2ind (sz, Y, X); endfunction %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,4]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "linear")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "linear")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,4]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "nearest")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "nearest")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; ## 'pchip' commented out since it is the same as 'cubic' %!#demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "pchip")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; ## 'pchip' commented out since it is the same as 'cubic' %!#demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "pchip")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "cubic")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "cubic")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! A = [13,-1,12;5,4,3;1,6,2]; %! x = [0,1,2]; y = [10,11,12]; %! xi = linspace (min (x), max (x), 17); %! yi = linspace (min (y), max (y), 26)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "spline")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!demo %! clf; %! colormap ("default"); %! [x,y,A] = peaks (10); %! x = x(1,:)'; y = y(:,1); %! xi = linspace (min (x), max (x), 41); %! yi = linspace (min (y), max (y), 41)'; %! mesh (xi,yi,interp2 (x,y,A,xi,yi, "spline")); %! [x,y] = meshgrid (x,y); %! hold on; plot3 (x,y,A,"b*"); hold off; %!test # simple test %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x, y); %! orig = X.^2 + Y.^3; %! xi = [1.2,2, 1.5]; %! yi = [6.2, 4.0, 5.0]'; %! %! expected = ... %! [243, 245.4, 243.9; %! 65.6, 68, 66.5; %! 126.6, 129, 127.5]; %! result = interp2 (x,y,orig, xi, yi); %! %! assert (result, expected, 1000*eps); %!test # 2^n refinement form %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x, y); %! orig = X.^2 + Y.^3; %! xi = [1:0.25:3]; yi = [4:0.25:7]'; %! expected = interp2 (x,y,orig, xi, yi); %! result = interp2 (orig, 2); %! %! assert (result, expected, 10*eps); %!test # matrix slice %! A = eye (4); %! assert (interp2 (A,[1:4],[1:4]), [1,1,1,1]); %!test # non-gridded XI,YI %! A = eye (4); %! assert (interp2 (A,[1,2;3,4],[1,3;2,4]), [1,0;0,1]); %!test # for values outside of boundaries %! x = [1,2,3]; %! y = [4,5,6,7]; %! [X, Y] = meshgrid (x,y); %! orig = X.^2 + Y.^3; %! xi = [0,4]; %! yi = [3,8]'; %! assert (interp2 (x,y,orig, xi, yi), [NA,NA;NA,NA]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 0), [0,0;0,0]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 2), [2,2;2,2]); %! assert (interp2 (x,y,orig, xi, yi,"spline", 2), [2,2;2,2]); %! assert (interp2 (x,y,orig, xi, yi,"linear", 0+1i), [0+1i,0+1i;0+1i,0+1i]); %! assert (interp2 (x,y,orig, xi, yi,"spline"), [27,43;512,528]); %!test # for values at boundaries %! A = [1,2;3,4]; %! x = [0,1]; %! y = [2,3]'; %! assert (interp2 (x,y,A,x,y,"linear"), A); %! assert (interp2 (x,y,A,x,y,"nearest"), A); %!test # for Matlab-compatible rounding for 'nearest' %! X = meshgrid (1:4); %! assert (interp2 (X, 2.5, 2.5, "nearest"), 3); ## re-order monotonically decreasing (bug #41838). %!assert (interp2 ([1 2 3], [3 2 1], magic (3), 2.5, 3), 3.5); %!assert (interp2 ([3 2 1], [1 2 3], magic (3), 1.5, 1), 3.5); %!shared z, zout, tol %! z = [1 3 5; 3 5 7; 5 7 9]; %! zout = [1 2 3 4 5; 2 3 4 5 6; 3 4 5 6 7; 4 5 6 7 8; 5 6 7 8 9]; %! tol = 2 * eps; %! %!assert (interp2 (z), zout, tol) %!assert (interp2 (z, "linear"), zout, tol) %!assert (interp2 (z, "pchip"), zout, tol) %!assert (interp2 (z, "cubic"), zout, 10 * tol) %!assert (interp2 (z, "spline"), zout, tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "linear"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "pchip"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "cubic"), repmat ([5, 7, 3], [3, 1]), 10 * tol) %!assert (interp2 (z, [2 3 1], [2 2 2]', "spline"), repmat ([5, 7, 3], [3, 1]), tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "linear"), [5 7 3], tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "pchip"), [5 7 3], tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "cubic"), [5 7 3], 10 * tol) %!assert (interp2 (z, [2 3 1], [2 2 2], "spline"), [5 7 3], tol) ## Test input validation %!error interp2 (1, 1, 1, 1, 1, 2) #only 5 numeric inputs %!error interp2 (1, 1, 1, 1, 1, 2, 2) #only 5 numeric inputs %!error <Z must be a 2-D matrix> interp2 ({1}) %!error <Z must be a 2-D matrix> interp2 (1,1,1) %!error <Z must be a 2-D matrix> interp2 (ones (2,2,2)) %!error <N must be an integer .= 0> interp2 (ones (2), ones (2)) %!error <N must be an integer .= 0> interp2 (ones (2), -1) %!error <N must be an integer .= 0> interp2 (ones (2), 1.5) %!warning <ignoring unsupported '\*' flag> interp2 (rand (3,3), 1, "*linear"); %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', {1}) %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', ones (2,2)) %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', "abc") %!error <EXTRAP must be a numeric scalar> interp2 (1, 1, 1, 1, 1, 'linear', "extrap") %!error <X, Y must be numeric matrices> interp2 ({1}, 1, ones (2), 1, 1) %!error <X, Y must be numeric matrices> interp2 (1, {1}, ones (2), 1, 1) %!error <XI, YI must be numeric> interp2 (1, 1, ones (2), {1}, 1) %!error <XI, YI must be numeric> interp2 (1, 1, ones (2), 1, {1}) %!error <X and Y must be matrices of equal size> interp2 (ones(2,2), 1, ones (2), 1, 1) %!error <X and Y must be matrices of equal size> interp2 (ones(2,2), ones(2,3), ones (2), 1, 1) %!error <X and Y size must match the dimensions of Z> interp2 (1:3, 1:3, ones (3,2), 1, 1) %!error <X and Y size must match the dimensions of Z> interp2 (1:2, 1:2, ones (3,2), 1, 1) %!error <X must be strictly monotonic> interp2 ([1 0 2], 1:3, ones (3,3), 1, 1) %!error <Y must be strictly monotonic> interp2 (1:3, [1 0 2], ones (3,3), 1, 1) %!error <XI and YI must be matrices of equal size> interp2 (1:2, 1:2, ones (2), ones(2,2), 1) %!error <XI and YI must be matrices of equal size> interp2 (1:2, 1:2, ones (2), 1, ones(2,2)) %!error <XI, YI must have uniform spacing> interp2 (1:2, 1:2, ones (2), [1 2 4], [1 2 3], "spline") %!error <XI, YI must have uniform spacing> interp2 (1:2, 1:2, ones (2), [1 2 3], [1 2 4], "spline") %!error interp2 (1, 1, 1, 1, 1, "foobar")