Decimal indexing for arrays in MATLAB

If I have a array of 11 elements, within the range 1 and 2, with a difference of 0.1, i.e, m = 1:0.1:2; to access the value of '1.4000' from the array 'm', the normal procedure is to write 'm(5)'. (index must be an integer)

Can I somehow index 'm(1.4)' and get the value 1.4000? (have a decimal value in the index)

[DGM]

What would be the point of getting the value in an array when, in order to get said value, you already know what it is?

This isn't real code, but hypothetically:

m = rand(100);
myindex = 0.504074886735144;
myvalue = m(myindex); % the result is either myindex or an error

In concept, this process accomplishes nothing except testing whether the value exists in the array.

On the other hand, maybe it's the location of the value that's important?

[Bjorn Gustavsson]

Sometimes I see 1-D interpolation that way - this require the array to have some simple interpretation of samples of a sufficiently smooth function that the samples in the array can be used to build useful estimates for your "fractional" indices. But indexing is to elements you have.

[Yuvarajendra Anjaneya Reddy]

@DGM Sorry for not being descriptive of my issue. I have a mesh grid [X,Y] = ndgrid (1:256, 1:256); and another matrix u = sin(X) + cos (Y); I have interpolated 10 values between every consequtive values in all the matrices.

If I need to access the value 'u' when X = 1.4, and Y = 2.8, i.e, u_interp(1.4, 2.8), then I have trouble, as I will have to create new Indices or run the interp2 command again to access the values. So, I thought decimal indexing would be a way..

[X,Y] = ndgrid (1:256, 1:256);
u = sin(X) + cos (Y);

%Interpolation
[Xq, Yq] = ndgrid(1:(1/10):256, 1:(1/10):256);
F = griddedInterpolant(X, Y, u, 'spline');
u_interp = F(Xq, Yq);

Answer 1

[Bjorn Gustavsson]

Have a look at the help and documentation for griddedInterpolant. That function might be what you're looking for. It creates a function that interpolates over a gridded data. For repeated calls this means that it has kept the structure for interpolation such that you won't redo all the set-up you'd do with repeated calls to interp2 again and again with repeated calls.

HTH

[Yuvarajendra Anjaneya Reddy]

@Bjorn Gustavsson Thank you for pointing me to the solution. This is what I was looking for.