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author | John W. Eaton <jwe@octave.org> |
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date | Sat, 07 Mar 2009 10:41:27 -0500 |
parents | b297b86f4ad9 |
children | 06cebb6c5dde |
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## Copyright (C) 2000, 2006, 2007, 2008, 2009 Kai Habel ## ## 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{x} =} gradient (@var{m}) ## @deftypefnx {Function File} {[@var{x}, @var{y}, @dots{}] =} gradient (@var{m}) ## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{m}, @var{s}) ## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{m}, @var{dx}, @var{dy}, @dots{}) ## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{f}, @var{x0}) ## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{f}, @var{x0}, @var{s}) ## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{f}, @var{x0}, @var{dx}, @var{dy}, @dots{}) ## ## Calculate the gradient of sampled data, or of a function. If @var{m} ## is a vector, calculate the one dimensional gradient of @var{m}. If ## @var{m} is a matrix the gradient is calculated for each row. ## ## @code{[@var{x}, @var{y}] = gradient (@var{m})} calculates the one ## dimensional gradient for each direction if @var{m} if @var{m} is a ## matrix. Additional return arguments can be use for multi-dimensional ## matrices. ## ## Spacing values between two points can be provided by the ## @var{dx}, @var{dy} or @var{h} parameters. If @var{h} is supplied it ## is assumed to be the spacing in all directions. Otherwise, separate ## values of the spacing can be supplied by the @var{dx}, etc variables. ## A scalar value specifies an equidistant spacing, while a vector value ## can be used to specify a variable spacing. The length must match ## their respective dimension of @var{m}. ## ## At boundary points a linear extrapolation is applied. Interior points ## are calculated with the first approximation of the numerical gradient ## ## @example ## y'(i) = 1/(x(i+1)-x(i-1)) *(y(i-1)-y(i+1)). ## @end example ## ## If the first argument @var{f} is a function handle, the gradient of the ## function at the points in @var{x0} is approximated using central ## difference. For example, @code{gradient (@@cos, 0)} approximates the ## gradient of the cosine function in the point @math{x0 = 0}. As with ## sampled data, the spacing values between the points from which the ## gradient is estimated can be set via the @var{s} or @var{dx}, ## @var{dy}, @dots{} arguments. By default a spacing of 1 is used. ## @end deftypefn ## Author: Kai Habel <kai.habel@gmx.de> ## Modified: David Bateman <dbateman@free.fr> Added NDArray support function varargout = gradient (m, varargin) if (nargin < 1) print_usage () endif nargout_with_ans = max(1,nargout); if (ismatrix (m)) [varargout{1:nargout_with_ans}] = matrix_gradient (m, varargin{:}); elseif (isa (m, "function_handle")) [varargout{1:nargout_with_ans}] = handle_gradient (m, varargin{:}); elseif (ischar(m)) [varargout{1:nargout_with_ans}] = handle_gradient (str2func (m), varargin{:}); else error ("gradient: first input must be an array or a function"); endif endfunction function varargout = matrix_gradient (m, varargin) transposed = false; if (isvector (m)) ## make a column vector. transposed = (size (m, 2) == 1); m = m(:)'; endif nd = ndims (m); sz = size (m); if (nargin > 2 && nargin != nd + 1) print_usage () endif d = cell (1, nd); if (nargin == 1) for i = 1:nd d{i} = ones (sz(i), 1); endfor elseif (nargin == 2) if (isscalar (varargin{1})) for i = 1:nd d{i} = varargin{1} * ones (sz(i), 1); endfor else for i = 1:nd d{i} = varargin{1}; endfor endif else for i = 1:nd if (isscalar (varargin{i})) ## Why the hell did Matlab decide to swap these two values? if (i == 1) d{2} = varargin{1} * ones (sz(2), 1); elseif (i == 2) d{1} = varargin{2} * ones (sz(1), 1); else d{i} = varargin{i} * ones (sz(i), 1); endif else ## Why the hell did Matlab decide to swap these two values? if (i == 1) d{2} = varargin{1}; elseif (i == 2) d{1} = varargin{2}; else d{i} = varargin{i}; endif endif endfor endif for i = 1:max (2, min (nd, nargout)) mr = sz(i); mc = prod ([sz(1:i-1), sz(i+1:nd)]); Y = zeros (size (m), class (m)); if (mr > 1) ## Top and bottom boundary. Y(1,:) = diff (m(1:2,:)) / d{i}(1); Y(mr,:) = diff (m(mr-1:mr,:)) / d{i}(mr-1); endif if (mr > 2) ## Interior points. Y(2:mr-1,:) = ((m(3:mr,:) - m(1:mr-2,:)) ./ kron (d{i}(1:mr-2) + d{i}(2:mr-1), ones (1, mc))); endif varargout{i} = ipermute (Y, [i:nd,1:i-1]); m = permute (m, [2:nd,1]); endfor ## Why the hell did Matlab decide to swap these two values? tmp = varargout{1}; varargout{1} = varargout{2}; varargout{2} = tmp; if (transposed) varargout{1} = varargout{1}.'; endif endfunction function varargout = handle_gradient (f, p0, varargin) ## Input checking p0_size = size (p0); if (numel (p0_size) != 2) error ("gradient: the second input argument should either be a vector or a matrix"); endif if (any (p0_size == 1)) p0 = p0 (:); dim = 1; num_points = numel (p0); else num_points = p0_size (1); dim = p0_size (2); endif if (length (varargin) == 0) delta = 1; elseif (length (varargin) == 1 || length (varargin) == dim) try delta = [varargin{:}]; catch error ("gradient: spacing parameters must be scalars or a vector"); end_try_catch else error ("gradient: incorrect number of spacing parameters"); endif if (isscalar (delta)) delta = repmat (delta, 1, dim); elseif (!isvector (delta)) error ("gradient: spacing values must be scalars or a vector"); endif ## Calculate the gradient p0 = mat2cell (p0, num_points, ones (1, dim)); varargout = cell (1,dim); for d = 1:dim s = delta (d); df_dx = (f (p0{1:d-1}, p0{d}+s, p0{d+1:end}) - f (p0{1:d-1}, p0{d}-s, p0{d+1:end})) ./ (2*s); if (dim == 1) varargout{d} = reshape (df_dx, p0_size); else varargout{d} = df_dx; endif endfor endfunction %!test %! data = [1, 2, 4, 2]; %! dx = gradient (data); %! assert (dx, [1, 3/2, 0, -2]); %!test %! x = 0:10; %! f = @cos; %! df_dx = @(x) -sin (x); %! assert (gradient (f, x), df_dx (x), 0.2); %! assert (gradient (f, x, 0.5), df_dx (x), 0.1); %!test %! xy = reshape (1:10, 5, 2); %! f = @(x,y) sin (x) .* cos (y); %! df_dx = @(x, y) cos (x) .* cos (y); %! df_dy = @(x, y) -sin (x) .* sin (y); %! [dx, dy] = gradient (f, xy); %! assert (dx, df_dx (xy (:, 1), xy (:, 2)), 0.1) %! assert (dy, df_dy (xy (:, 1), xy (:, 2)), 0.1)