MATLAB: Is table performance still the slowest in MALTAB R2019b

performancer2019btable

Hey all

MALTAB has announced that table has large performance improvements in R2019, from my experience, table used to be the slowest, worse one among array, struct and table.

Is there anyone has compared performance among array, struct and table in R2019?

Thanks

Kathy

Best Answer

Tables will always be slower than struct. I guarantee it.

Related Solutions

MATLAB: MapSolution broken in R2019b

Hi Matt and Walter,

Firstly Matt, many apologies that you've run into this unintended behavior. Also, many thanks to you both for looking into this and flagging it up.

What has happened here? The short answer is that mapSolution was made an internal function in R2019a and replaced with varindex. Once we made mapSolution internal, we repurposed it in R2019b leading to the internal error you encountered. We will tidy up the error and add a note in the documentation pointing you to varindex

Matt's original code works with varindex

%% Define the variables
x=optimvar('x',{'x1','x2'},'LowerBound',[-100,-200]);
y=optimvar('y',1,3,'LowerBound',[0 0 0],'UpperBound',[+300,+400,+500]);
  
%% Define some constraints
C.inequ=2*sum(y)+sum(x)<=1000;
C.equ=5*sum(x)==100;
            
           
prob=optimproblem('Constraints',C,'Objective',sum(x)+sum(y));
idx = varindex(prob);

Resulting in the output

idx = 
  struct with fields:
    x: [1 2]
    y: [3 4 5]

Also, varindex allows you to get the variable index by name, e.g.

idx = varindex(prob, 'y')

Resulting a double as the output

idx =
     3     4     5

Matt, may I ask if you were aware of varindex? Also, is there anything in mapSolution that you are relying on that varindex doesn't provide?

Thanks again for flagging this and hope varindex helps!

Cheers,

Paul

Documentation for varindex:

https://uk.mathworks.com/help/optim/ug/optim.problemdef.optimizationproblem.varindex.html

MATLAB: How Matlab access data in nested structures

For a situation like this, code readability and adaptability is much more important than performance. Even if one of these methods is slightly faster than the other, the compute time saved is not worth the extra time you will spend trying to make changes when the requirements for your project change.

If you have hundreds of variables, you also might want to think about completely restructuring your program. Use functions so that each variable is only defined and used where it needs to be, or use a different data structure that better matches your data.

Once the program is done, and if performance is still an issue, you can use the profiler to identify the bottlenecks. I guarantee it won't be the structures.

Best Answer

Related Solutions

MATLAB: MapSolution broken in R2019b

MATLAB: How Matlab access data in nested structures

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