How to fine numerical gradient
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I have a function f(x,y). Following is just a sample function explaining how I save f(x,y) value in a 2D array.
clear; clc;
xs = linspace(1,2,100);
ys = linspace(1,3,100);
fun_values = zeros(100,100);
for ix = 1:100
x = xs(ix);
for iy = 1:100
y = ys(iy);
fun_values(ix,iy) = x^2+y^2;
end
end
I want to calculate 
and 
. I am confused what is the correct way to use gradient() function given the way how I store values in fun_values variable.
and . I am confused what is the correct way to use gradient() function given the way how I store values in fun_values variable.采纳的回答
Chunru
2024-3-21
clear; clc;
xs = linspace(1,2,100);
ys = linspace(1,3,100)'; % transpose here
fun_values = zeros(100,100);
%{
for ix = 1:100
x = xs(ix);
for iy = 1:100
y = ys(iy);
fun_values(ix,iy) = x^2+y^2;
end
end
%}
% Try use array operation instead of loops
fun_values = xs.^2 + ys.^2;
% Gradient
[Fx, Fy] = gradient(fun_values, xs, ys);
更多回答（1 个）
There is another way to find the numerical gradient for the given function
clear; clc;
xs = linspace(1,2,100);
ys = linspace(1,3,100)'; % transpose here
fun_values = zeros(100,100);
[Xs, Ys] = meshgrid(xs,ys);
% Try use array operation instead of loops
fun_values = Xs.^2 + Ys.^2;
% Gradient
[Fx, Fy] = gradient(fun_values)
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