How to derive and plot derive for a set of data with non linear x axis?

Hello, I have a 54x2 table for x axis and y axis. The x axis is data is non linear ( for example the first three points are 20327,20328,20329, and the fourth point is 22516, then 22517,22518,25832...) How can I plot the data and derive and plot the derivtive without linearly interpolation (so it does not fill or connect the missing points in the x axis)?

Answer 1

[Star Strider]

I have no idea what the data are.

Calculationg the numerical derivative is straightforward with the gradient function —

x = sort(rand(1,20));
y = rand(size(x));

figure
plot(x, y)
grid
xlabel('x')
ylabel('y')
title('Data')

dydx = gradient(y) ./ gradient(x);

figure
plot(x, dydx)
grid
xlabel('x')
ylabel('$\frac{dy}{dx}$', 'Interpreter','latex')
title('Derivative')

The independent variable data do not need to be evenly-spaced.

.

[Youssif Youssif]

Heres an picture of the data, you can see that the X data is not linear, I was looking to plot it and its derivative with the data being linearly interpolated (filling in gaps where there is no data)

[Star Strider]

I cannot do anything with an image of data.

The approach to ‘filling in gaps where there is no data’ is going to be a bit difficult, and likely depends on how you want to interpolate the ‘missing’ values.

One approach —

x = sort(rand(1,20));
y = rand(size(x));

figure
plot(x, y)
grid
xlabel('x')
ylabel('y')
title('Data')

xq = linspace(min(x), max(x), 150);
yq = interp1(x, y, xq, 'makima');                   % Choose The Appropriate Interpolation Method For Your Data

figure
plot(xq, yq)
grid
xlabel('x')
ylabel('y')
title('interpolated Data')

dydx = gradient(yq) ./ gradient(xq);

figure
plot(xq, dydx)
grid
xlabel('x')
ylabel('$\frac{dy}{dx}$', 'Interpreter','latex')
title('Derivative of Interpolated Data')

See the documentation on interp1 for details and for different interpolationo methods.

.