MatLab: How to add a matrix to a structure without a loop?

In summary, you can create a 1000x3 matrix "X" to copy into a structure, using the .* command. The structure would have fields for time, meanJulianDate, position, and velocity.
  • #1
Bruce-Almight
4
0
Hi,

I have a structure AA.BB, which goes from AA.BB(1) to AA.BB(1000). I have for example a matrix "X" of size [1000x3], which I want to add to this structure, such that it becomes like this:

AA.BB(1).X(1)​
AA.BB(2).X(1)​
...​
AA.BB(1000).X(1)​

I want the same for X(2) and X(3).

Can this be done without using a loop, in which all entries of the matrix are individually placed in the structure? I don't want to use a loop at all.

I know it may be easier to just keep the matrix "X", but I want to know if such a thing can be done.

Thanks in advance for your help!
 
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  • #2
I have a structure AA.BB, which goes from AA.BB(1) to AA.BB(1000).
Do you mean you have a vector of length 1000?
To multiply individual elements of a vector with a matrix you use the command '.*'
note the dot, this is important.
I have done a wee demonstration to help you with your problem. Just adapt it to move into 3 column matrix regime. I have just made a small matrix 'x' and a small vector 'y'. Shown below is how to multiply a row or column of x by y:

----------------------------
>> y=[2 2]

y =

2 2

>> x=[1 2;3 4]

x =

1 2
3 4

>> x(1,:)

ans =

1 2

>> x(:,1)

ans =

1
3

>> x(1,:).*y

ans =

2 4
----------------------------
Hope this helps you out :approve:
 
  • #3
I know the command .*, but don't think it is really what I need. I need to copy the matrix I have into a structure, but it gives errors, which I will post later in this message.

I have this structure AA.BB. This BB has to go from 1 to 1000, which are indications for time steps in a simulation. For each time step, there are many characteristics that are in the structure.

As an example, for the first time step the structure looks like this:

AA.BB(1).cc​
AA.BB(1).dd​
AA.BB(1).ee​
AA.BB(1).ff​
AA.BB(1).gg​

and so on...

For the second time step, these characteristics (cc, dd, ee, ff, gg) have some different values:

AA.BB(2).cc​
AA.BB(2).dd​
AA.BB(2).ee​
AA.BB(2).ff​
AA.BB(2).gg​

Now I have a matrix "X", which has 1000 rows (one row for each separate time step) and 3 columns (representing the x-, y- and z-coordinate of some parameter).

This matrix "X" has to be copied somehow into the structure without a loop. What I want to get, for example for the first time step:

AA.BB(1).X(1)​
AA.BB(1).X(2)​
AA.BB(1).X(3)​

For the second time step:

AA.BB(2).X(1)​
AA.BB(2).X(2)​
AA.BB(2).X(3)​

What I have tried is the following commands:

AA.BB(: ).X(1) = X(:,1);
AA.BB(: ).X(2) = X(:,2);
AA.BB(: ).X(3) = X(:,3);

This gives the following error message:

? Scalar index required for this type of multi-level indexing.

Can it be done another way, without a loop?
 
  • #4
Wouldn't any matrix procedure involving multiple elements at the computational level involve a loop of some sort, due to the nature of having more than one element?

Either way, you may wish to read up on MathWorks' built in documentation on the "struct" command. If I recall, it should allow you to pre-allocate the structure layout and the structural elements through a series of matrices and cell arrays/non cell inputs (easy to convert).
 
  • #5
I need to copy the matrix I have into a structure,
Elaboration of structure would be helpful
 
  • #6
The AA.BB structure is called spacecraft .model in my own simulation. It will be a 1x1000 structure with the following fields:

time
meanJulianDate
position
velocity​

I have the following matrices:

t [1000x1]
MJD [1000x1]
r [1000x3]
V [1000x3]​

Using a loop I can easily fill the structure:

for i = 1:1000

spacecraft .model(i).time = t(i,1)
spacecraft .model(i).meanJulianDate = MJD(i,1)
spacecraft .model(i).position = r(i,1:3)
spacecraft .model(i).velocity = V(i,1:3)​
end​

Question is, how to do the same thing without the use of a loop? I'm just wondering if this is possible and if so, how.
 

FAQ: MatLab: How to add a matrix to a structure without a loop?

1. How do I add a matrix to a structure in MatLab without using a loop?

There are a few ways to add a matrix to a structure in MatLab without using a loop. One option is to use the structfun function, which applies a specified function to each field of the structure. Another option is to use the cell2struct function, which converts a cell array into a structure. Both of these methods allow you to add a matrix to a structure without using a loop.

2. Can I use the struct function to add a matrix to a structure without a loop?

Yes, you can use the struct function to add a matrix to a structure without a loop. This function allows you to create a structure with specified fields and values, including matrices. However, if you already have an existing structure that you want to add a matrix to, you may need to use one of the other methods mentioned in the first question.

3. How do I specify the field name when adding a matrix to a structure in MatLab?

When using the structfun or cell2struct functions, you can specify the field name as the first argument, followed by the matrix you want to add. For example, if you want to add a matrix called A to a structure called myStruct with the field name myMatrix, you would use the syntax myStruct = structfun(@(x) A, 'myMatrix'). You can also use the setfield function to specify the field name when adding a matrix to a structure.

4. Can I add multiple matrices to a structure at once without using a loop in MatLab?

Yes, you can add multiple matrices to a structure at once without using a loop in MatLab. One way to do this is by using the struct function, which allows you to specify multiple fields and values in one line of code. You can also use the deal function to assign multiple matrices to fields in a structure.

5. Is there a performance benefit to adding a matrix to a structure without using a loop in MatLab?

In general, using built-in functions like structfun or cell2struct to add a matrix to a structure can be more efficient and faster than using a loop. This is because these functions are optimized for handling large data sets and can avoid the overhead of looping through each element one at a time. However, the performance benefit may vary depending on the specific implementation and the size of the data being manipulated.

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