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📄 interp2.m

📁 数值类综合算法 常用数值计算工具包(龙贝格算法、改进欧拉法、龙格库塔方法、复合辛普森)
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function zi = interp2(varargin)
%二元函数网格数据的插值
%ZI=interp2(X,Y,Z,XI,YI,'方法')  求二元函数z=f(x,y)的插值. 
%   这里X,Y,Z是同维数矩阵表示网格数据,XI,YI,ZI是同维数矩阵表示插值点.
%或ZI=interp2(x,y,z,xi,yi)其中,x,xi为行向量,y,yi为列向量.
%  'bilinear',使用双线性插值(默认)
%  'spline' 使用二元三次样条插值.
%  'cubic' 使用二元三次插值.
%例如
%   clear;close;x=0:4;y=2:4;
%   Z=[82 81 80 82 84;79 63 61 65 81;84 84 82 85 86];
%   [X,Y]=meshgrid(x,y);
%   subplot(2,1,1);
%   mesh(X,Y,Z);title('RAW DATA');
%   xi=0:0.1:4;yi=2:0.2:4;
%   [XI,YI]=meshgrid(xi,yi);
%   zspline=interp2(x,y,z,XI,YI,'spline');
%   subplot(2,1,2);
%   mesh(XI,YI,zspline);
%   title('SPLINE');
%
%INTERP2 2-D interpolation (table lookup).
%   ZI = INTERP2(X,Y,Z,XI,YI) interpolates to find ZI, the values of the
%   underlying 2-D function Z at the points in matrices XI and YI.
%   Matrices X and Y specify the points at which the data Z is given.
%   Out of range values are returned as NaN.
%
%   XI can be a row vector, in which case it specifies a matrix with
%   constant columns. Similarly, YI can be a column vector and it 
%   specifies a matrix with constant rows. 
%
%   ZI = INTERP2(Z,XI,YI) assumes X=1:N and Y=1:M where [M,N]=SIZE(Z).
%   ZI = INTERP2(Z,NTIMES) expands Z by interleaving interpolates between
%   every element, working recursively for NTIMES.  INTERP2(Z) is the
%   same as INTERP2(Z,1).
%
%   ZI = INTERP2(...,'method') specifies alternate methods.  The default
%   is linear interpolation.  Available methods are:
%
%     'nearest' - nearest neighbor interpolation
%     'linear'  - bilinear interpolation
%     'cubic'   - bicubic interpolation
%     'spline'  - spline interpolation
%
%   All the interpolation methods require that X and Y be monotonic and
%   plaid (as if they were created using MESHGRID).  X and Y can be
%   non-uniformly spaced.  For faster interpolation when X and Y are
%   equally spaced and monotonic, use the methods '*linear', '*cubic', or
%   '*nearest'.
%
%   For example, to generate a coarse approximation of PEAKS and
%   interpolate over a finer mesh:
%       [x,y,z] = peaks(10); [xi,yi] = meshgrid(-3:.1:3,-3:.1:3);
%       zi = interp2(x,y,z,xi,yi); mesh(xi,yi,zi)
%      
%   See also INTERP1, INTERP3, INTERPN, MESHGRID, GRIDDATA.

%   Copyright (c) 1984-98 by The MathWorks, Inc.
%   $Revision: 5.26 $

error(nargchk(1,6,nargin));

bypass = 0;
uniform = 1;
if isstr(varargin{end}),
  narg = nargin-1;
  method = [varargin{end} '    ']; % Protect against short string.
  if method(1)=='*', % Direct call bypass.
    if method(2)=='l' | all(method(2:4)=='bil'), % bilinear interpolation.
      zi = linear(varargin{1:end-1});
      return

    elseif method(2)=='c' | all(method(2:4)=='bic'), % bicubic interpolation
      zi = cubic(varargin{1:end-1});
      return

    elseif method(2)=='n', % Nearest neighbor interpolation
      zi = nearest(varargin{1:end-1});
      return
    
    elseif method(2)=='s', % spline interpolation
      method = 'spline'; bypass = 1;

    else
      error([deblank(method),' is an invalid method.']);

    end
  elseif method(1)=='s', % Spline interpolation
    method = 'spline'; bypass = 1;
  end

else
  narg = nargin;
  method = 'linear';
end

if narg==1, % interp2(z), % Expand Z
  [nrows,ncols] = size(varargin{1});
  xi = 1:.5:ncols; yi = (1:.5:nrows)';
  x = 1:ncols; y = (1:nrows);
  [msg,x,y,z,xi,yi] = xyzchk(x,y,varargin{1},xi,yi);

elseif narg==2. % interp2(z,n), Expand Z n times
  [nrows,ncols] = size(varargin{1});
  ntimes = floor(varargin{2}(1));
  xi = 1:1/(2^ntimes):ncols; yi = (1:1/(2^ntimes):nrows)';
  x = 1:ncols; y = (1:nrows);
  [msg,x,y,z,xi,yi] = xyzchk(x,y,varargin{1},xi,yi);

elseif narg==3, % interp2(z,xi,yi)
  [nrows,ncols] = size(varargin{1});
  x = 1:ncols; y = (1:nrows);
  [msg,x,y,z,xi,yi] = xyzchk(x,y,varargin{1:3});

elseif narg==4,
  error('Wrong number of input arguments.');

elseif narg==5, % linear(x,y,z,xi,yi)
  [msg,x,y,z,xi,yi] = xyzchk(varargin{1:5});

end

if ~isempty(msg), error(msg); end

%
% Check for plaid data.
%
xx = x(1,:); yy = y(:,1);
if (size(x,2)>1 & ~isequal(repmat(xx,size(x,1),1),x)) | ...
   (size(y,1)>1 & ~isequal(repmat(yy,1,size(y,2)),y)),
  error(sprintf(['X and Y must be matrices produced by MESHGRID. Use' ...
     ' GRIDDATA instead \nof INTERP2 for scattered data.']));
end

%
% Check for non-equally spaced data.  If so, map (x,y) and
% (xi,yi) to matrix (row,col) coordinate system.
%
if ~bypass,
  xx = xx.'; % Make sure it's a column.
  dx = diff(xx); dy = diff(yy);
  xdiff = max(abs(diff(dx))); if isempty(xdiff), xdiff = 0; end
  ydiff = max(abs(diff(dy))); if isempty(ydiff), ydiff = 0; end
  if (xdiff > eps*max(abs(xx))) | (ydiff > eps*max(abs(yy))),
    if any(dx < 0), % Flip orientation of data so x is increasing.
      x = fliplr(x); y = fliplr(y); z = fliplr(z);
      xx = flipud(xx); dx = -flipud(dx);
    end
    if any(dy < 0), % Flip orientation of data so y is increasing.
      x = flipud(x); y = flipud(y); z = flipud(z);
      yy = flipud(yy); dy = -flipud(dy);
    end
  
    if any(dx<=0) | any(dy<=0), 
      error('X and Y must be monotonic vectors or matrices produced by MESHGRID.');
    end
  
    % Bypass mapping code for cubic
    if method(1)~='c', 
      % Determine the nearest location of xi in x
      [xxi,j] = sort(xi(:));
      [dum,i] = sort([xx;xxi]);
      ui(i) = (1:length(i));
      ui = (ui(length(xx)+1:end)-(1:length(xxi)))';
      ui(j) = ui;
    
      % Map values in xi to index offset (ui) via linear interpolation
      ui(ui<1) = 1;
      ui(ui>length(xx)-1) = length(xx)-1;
      ui = ui + (xi(:)-xx(ui))./(xx(ui+1)-xx(ui));
     
      % Determine the nearest location of yi in y
      [yyi,j] = sort(yi(:));
      [dum,i] = sort([yy;yyi(:)]);
      vi(i) = (1:length(i));
      vi = (vi(length(yy)+1:end)-(1:length(yyi)))';
      vi(j) = vi;
    
      % Map values in yi to index offset (vi) via linear interpolation
      vi(vi<1) = 1;
      vi(vi>length(yy)-1) = length(yy)-1;
      vi = vi + (yi(:)-yy(vi))./(yy(vi+1)-yy(vi));
      
      [x,y] = meshgrid(1:size(x,2),1:size(y,1));
      xi(:) = ui; yi(:) = vi;
    else
      uniform = 0;
    end
  end
end

% Now do the interpolation based on method.
method = [lower(method),'   ']; % Protect against short string

if method(1)=='l' | all(method(1:3)=='bil'), % bilinear interpolation.
  zi = linear(x,y,z,xi,yi);

elseif method(1)=='c' | all(method(1:3)=='bic'), % bicubic interpolation
  if uniform
    zi = cubic(x,y,z,xi,yi);
  else
    d = find(xi < min(x(:)) | xi > max(x(:)) | ...
             yi < min(y(:)) | yi > max(y(:)));
    zi = spline2(x,y,z,xi,yi);
    zi(d) = NaN;
  end

elseif method(1)=='n', % Nearest neighbor interpolation
  zi = nearest(x,y,z,xi,yi);

elseif method(1)=='s', % Spline interpolation
  zi = spline2(x,y,z,xi,yi);

else
  error([deblank(method),' is an invalid method.']);

end

%------------------------------------------------------
function F = linear(arg1,arg2,arg3,arg4,arg5)
%LINEAR 2-D bilinear data interpolation.
%   ZI = LINEAR(X,Y,Z,XI,YI) uses bilinear interpolation to
%   find ZI, the values of the underlying 2-D function in Z at the points
%   in matrices XI and YI.  Matrices X and Y specify the points at which 
%   the data Z is given.  X and Y can also be vectors specifying the 
%   abscissae for the matrix Z as for MESHGRID. In both cases, X
%   and Y must be equally spaced and monotonic.
%
%   Values of NaN are returned in ZI for values of XI and YI that are 
%   outside of the range of X and Y.
%
%   If XI and YI are vectors, LINEAR returns vector ZI containing
%   the interpolated values at the corresponding points (XI,YI).
%
%   ZI = LINEAR(Z,XI,YI) assumes X = 1:N and Y = 1:M, where
%   [M,N] = SIZE(Z).
%
%   ZI = LINEAR(Z,NTIMES) returns the matrix Z expanded by interleaving
%   bilinear interpolates between every element, working recursively
%   for NTIMES.  LINEAR(Z) is the same as LINEAR(Z,1).
%
%   This function needs about 4 times SIZE(XI) memory to be available.
%
%   See also INTERP2, CUBIC.

%   Clay M. Thompson 4-26-91, revised 7-3-91, 3-22-93 by CMT.

if nargin==1, % linear(z), Expand Z
  [nrows,ncols] = size(arg1);
  s = 1:.5:ncols; sizs = size(s);
  t = (1:.5:nrows)'; sizt = size(t);
  s = s(ones(sizt),:);
  t = t(:,ones(sizs));

elseif nargin==2, % linear(z,n), Expand Z n times
  [nrows,ncols] = size(arg1);
  ntimes = floor(arg2);
  s = 1:1/(2^ntimes):ncols; sizs = size(s);
  t = (1:1/(2^ntimes):nrows)'; sizt = size(t);
  s = s(ones(sizt),:);
  t = t(:,ones(sizs));

elseif nargin==3, % linear(z,s,t), No X or Y specified.
  [nrows,ncols] = size(arg1);
  s = arg2; t = arg3;

elseif nargin==4,
  error('Wrong number of input arguments.');

elseif nargin==5, % linear(x,y,z,s,t), X and Y specified.
  [nrows,ncols] = size(arg3);
  mx = prod(size(arg1)); my = prod(size(arg2));
  if any([mx my] ~= [ncols nrows]) & ...
     ~isequal(size(arg1),size(arg2),size(arg3))
    error('The lengths of the X and Y vectors must match Z.');
  end
  if any([nrows ncols]<[2 2]), error('Z must be at least 2-by-2.'); end
  s = 1 + (arg4-arg1(1))/(arg1(mx)-arg1(1))*(ncols-1);

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