| k-Wave Toolbox |
|
Calculate the gradient using a Fourier spectral method
fx = gradient(f, dx) fx = gradient(f, dx, [], deriv_order) fn = gradient(f, dn, dim) fn = gradient(f, dn, dim, deriv_order) [fx, fy] = gradient(f, dn) [fx, fy] = gradient(f, dn, [], deriv_order) [fx, fy, fz, ...] = gradient(f, dn) [fx, fy, fz, ...] = gradient(f, dn, [], deriv_order)
gradientSpect calculates the gradient of an n-dimensional input matrix using the Fourier collocation spectral method. The gradient for singleton dimensions is returned as 0.
A 1D example:
% compute gradient of a 2 period sinusoid
x = pi/20:pi/20:4*pi;
y = sin(x);
dydx = gradientSpect(y, pi/20);
% plot gradient and error compared to analytical solution
subplot(2, 1, 1), plot(x, cos(x), 'k-', x, dydx, 'bx');
axis tight;
title('dy/dx');
subplot(2, 1, 2), plot(x, cos(x) - dydx, 'k-');
axis tight;
title('Relative Error');

A modification of the example given with the MATLAB gradient function (x and y are reversed):
[x, y] = meshgrid(-2:.2:2, -2:.2:2); z = x .* exp(-x.^2 - y.^2); [px, py] = gradientSpect(z, [.2, .2]); contour(z) hold on; quiver(py, px); hold off;

|
matrix or vector to find the gradient of |
|
array of values for the grid point spacing in each dimension. If a value for |
|
optional input to specify a single dimension over which to compute the gradient for n-dimension input functions |
|
order of the derivative to compute, e.g., use 1 to compute df/dx, 2 to compute df^2/dx^2, etc. (default = 1) |
|
gradient in the each dimension, where x corresponds to dim = 1, y corresponds to dim = 2 etc. |
getFDMatrix, gradient, gradientFD
|
gradientFD | grid2cart | ![]() |
© 2009-2014 Bradley Treeby and Ben Cox.