Hello ! One possibility :
function [grad_x, grad_y] = compute_gradients(dem) diff_x = diff(dem, 1, 'c'); diff_y = diff(dem, 1, 'r'); grad_x = zeros(dem); grad_x(:, 2 : $-1) = (diff_x(:,1:$-1) + diff_x(:,2:$)) / 2; grad_x(:, 1) = diff_x(:,1); grad_x(:, $) = diff_x(:,$); grad_y = zeros(dem); grad_y(2 : $-1,:) = (diff_y(1:$-1,:) + diff_y(2:$,:)) / 2; grad_y(1,:) = diff_y(1,:); grad_y($,:) = diff_y($,:); endfunction Alain From: users <users-boun...@lists.scilab.org> On Behalf Of Lester Anderson Sent: vendredi 5 avril 2024 12:26 To: International users mailing list for Scilab. <users@lists.scilab.org> Subject: [Scilab-users] Compute gradients of grid data Hello, I am looking to create a hillshade function, but issues arise defining the the X and Y gradients. The test code so far: function [grad_x, grad_y] = compute_gradients(dem) grad_x = diff(dem, 1, 'c'); grad_y = diff(dem, 1, 'r'); endfunction // Create a test DEM grid dem=[1.23 1.45 1.67 1.89 2.10;... 1.54 1.73 1.92 2.11 2.30;... 1.85 2.01 2.17 2.33 2.49;... 2.16 2.29 2.42 2.55 2.68]; // Compute gradient [grad_x, grad_y] = compute_gradients(dem); // Display the results disp('Gradient in x-direction:'); disp(grad_x); disp('Gradient in y-direction:'); disp(grad_y); function slope = compute_slope(grad_x, grad_y) // Compute magnitude of gradient vector magnitude = sqrt(grad_x.^2 + grad_y.^2); // Compute slope using arctangent slope = atan(magnitude); endfunction slope = compute_slope(grad_x, grad_y); disp(slope) How to make the grad_x and grad_y matrices the same size? One route may be central differences as a method: function [grad_x, grad_y] = calculate_gradient(Z) [m, n] = size(Z); grad_x = zeros(m, n); grad_y = zeros(m, n); for i = 2:(m-1) for j = 2:(n-1) grad_x(i, j) = (Z(i+1, j) - Z(i-1, j)) / 2; grad_y(i, j) = (Z(i, j+1) - Z(i, j-1)) / 2; end end endfunction Any suggestions how to gradients for grid data. Thanks Lester This email and any attachments are intended solely for the use of the individual or entity to whom it is addressed and may be confidential and/or privileged. If you are not one of the named recipients or have received this email in error, (i) you should not read, disclose, or copy it, (ii) please notify sender of your receipt by reply email and delete this email and all attachments, (iii) Dassault Systèmes does not accept or assume any liability or responsibility for any use of or reliance on this email. Please be informed that your personal data are processed according to our data privacy policy as described on our website. Should you have any questions related to personal data protection, please contact 3DS Data Protection Officer https://www.3ds.com/privacy-policy/contact/ This email and any attachments are intended solely for the use of the individual or entity to whom it is addressed and may be confidential and/or privileged. If you are not one of the named recipients or have received this email in error, (i) you should not read, disclose, or copy it, (ii) please notify sender of your receipt by reply email and delete this email and all attachments, (iii) Dassault Systèmes does not accept or assume any liability or responsibility for any use of or reliance on this email. Please be informed that your personal data are processed according to our data privacy policy as described on our website. Should you have any questions related to personal data protection, please contact 3DS Data Protection Officer https://www.3ds.com/privacy-policy/contact/
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