X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?p=CreaPhase.git;a=blobdiff_plain;f=octave_packages%2Fm%2Fgeneral%2Fgradient.m;fp=octave_packages%2Fm%2Fgeneral%2Fgradient.m;h=9e662670bb6442b873ed447377e1462b156bf9c3;hp=0000000000000000000000000000000000000000;hb=1c0469ada9531828709108a4882a751d2816994a;hpb=63de9f36673d49121015e3695f2c336ea92bc278
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+## Copyright (C) 2000-2012 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
+## .
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{dx} =} gradient (@var{m})
+## @deftypefnx {Function File} {[@var{dx}, @var{dy}, @var{dz}, @dots{}] =} gradient (@var{m})
+## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{m}, @var{s})
+## @deftypefnx {Function File} {[@dots{}] =} gradient (@var{m}, @var{x}, @var{y}, @var{z}, @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{x}, @var{y}, @dots{})
+##
+## Calculate the gradient of sampled data or 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 dimension.
+##
+## @code{[@var{dx}, @var{dy}] = gradient (@var{m})} calculates the one
+## dimensional gradient for @var{x} and @var{y} direction if @var{m} is a
+## matrix. Additional return arguments can be use for multi-dimensional
+## matrices.
+##
+## A constant spacing between two points can be provided by the
+## @var{s} parameter. If @var{s} is a scalar, it is assumed to be the spacing
+## for all dimensions.
+## Otherwise, separate values of the spacing can be supplied by
+## the @var{x}, @dots{} arguments. Scalar values specify an equidistant
+## spacing.
+## Vector values for the @var{x}, @dots{} arguments specify the coordinate for
+## that
+## dimension. 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.
+## @seealso{diff, del2}
+## @end deftypefn
+
+## Author: Kai Habel
+## Modified: David Bateman 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 row vector.
+ transposed = (size (m, 2) == 1);
+ m = m(:).';
+ endif
+
+ nd = ndims (m);
+ sz = size (m);
+ if (length(sz) > 1)
+ tmp = sz(1); sz(1) = sz(2); sz(2) = tmp;
+ endif
+
+ if (nargin > 2 && nargin != nd + 1)
+ print_usage ();
+ endif
+
+ ## cell d stores a spacing vector for each dimension
+ d = cell (1, nd);
+ if (nargin == 1)
+ ## no spacing given - assume 1.0 for all dimensions
+ for i = 1:nd
+ d{i} = ones (sz(i) - 1, 1);
+ endfor
+ elseif (nargin == 2)
+ if (isscalar (varargin{1}))
+ ## single scalar value for all dimensions
+ for i = 1:nd
+ d{i} = varargin{1} * ones (sz(i) - 1, 1);
+ endfor
+ else
+ ## vector for one-dimensional derivative
+ d{1} = diff (varargin{1}(:));
+ endif
+ else
+ ## have spacing value for each dimension
+ if (length(varargin) != nd)
+ error ("gradient: dimensions and number of spacing values do not match");
+ endif
+ for i = 1:nd
+ if (isscalar (varargin{i}))
+ d{i} = varargin{i} * ones (sz(i) - 1, 1);
+ else
+ d{i} = diff (varargin{i}(:));
+ endif
+ endfor
+ endif
+
+ m = shiftdim (m, 1);
+ for i = 1:min (nd, nargout)
+ mr = rows (m);
+ mc = numel (m) / mr;
+ 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
+
+ ## turn multi-dimensional matrix in a way, that gradient
+ ## along x-direction is calculated first then y, z, ...
+
+ if (i == 1)
+ varargout{i} = shiftdim (Y, nd - 1);
+ m = shiftdim (m, nd - 1);
+ elseif (i == 2)
+ varargout{i} = Y;
+ m = shiftdim (m, 2);
+ else
+ varargout{i} = shiftdim (Y, nd - i + 1);
+ m = shiftdim (m, 1);
+ endif
+ endfor
+
+ 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);
+%! dx2 = gradient (data, 0.25);
+%! dx3 = gradient (data, [0.25, 0.5, 1, 3]);
+%! assert (dx, [1, 3/2, 0, -2]);
+%! assert (dx2, [4, 6, 0, -8]);
+%! assert (dx3, [4, 4, 0, -1]);
+%! assert (size_equal(data, dx));
+
+%!test
+%! [Y,X,Z,U] = ndgrid (2:2:8,1:5,4:4:12,3:5:30);
+%! [dX,dY,dZ,dU] = gradient (X);
+%! assert (all(dX(:)==1));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (Y);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==2));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (Z);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==4));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (U);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==5));
+%! assert (size_equal(dX, dY, dZ, dU, X, Y, Z, U));
+%! [dX,dY,dZ,dU] = gradient (U, 5.0);
+%! assert (all(dU(:)==1));
+%! [dX,dY,dZ,dU] = gradient (U, 1.0, 2.0, 3.0, 2.5);
+%! assert (all(dU(:)==2));
+
+%!test
+%! [Y,X,Z,U] = ndgrid (2:2:8,1:5,4:4:12,3:5:30);
+%! [dX,dY,dZ,dU] = gradient (X+j*X);
+%! assert (all(dX(:)==1+1j));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (Y-j*Y);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==2-j*2));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (Z+j*1);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==4));
+%! assert (all(dU(:)==0));
+%! [dX,dY,dZ,dU] = gradient (U-j*1);
+%! assert (all(dX(:)==0));
+%! assert (all(dY(:)==0));
+%! assert (all(dZ(:)==0));
+%! assert (all(dU(:)==5));
+%! assert (size_equal(dX, dY, dZ, dU, X, Y, Z, U));
+%! [dX,dY,dZ,dU] = gradient (U, 5.0);
+%! assert (all(dU(:)==1));
+%! [dX,dY,dZ,dU] = gradient (U, 1.0, 2.0, 3.0, 2.5);
+%! assert (all(dU(:)==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)
+