What tomSym cannot do

There are a few things that are possible in Matlab code, but which tomSym currently cannot do. Below we list the most common issues, and their work-arounds.

Variable-size matrixes

The size of a tomSym object cannot depend on the value of another tomSym object. This has to do with the fact that numeric solvers typically allocate memory only at the start of an optimization run, and then expect the number of unknowns to remain constant. (This may change in the future.)

N-dimensional arrays for N > 2

TOMSYM works with scalars, vectors, and two-dimensional matrices. Although Matlab can handle arrays of any dimension, TOMSYM cannot. The work-around is to use tomArray, which transforms tomSym symbols into arrays of any dimension. (TomArray also allows for a GAMS-style indexing which is a bit different from Matlab syntax, but convenient when formulating optimization problems involving high-dimension arrays.)

Note that TOMSYM supports interpn with high-dimensional numeric data, although the symbolic inputs must be of dimension less than two.

Limits

TOMSYM evaluates expressions by generating matlab code. (It does some mathematical simplification to improve efficiency, but only to a limited extent.) If an expression evaluates to 0/0 or 0*Inf, then NaN (Not a Number) will be returned. When the solver encounters a NaN, it will often just quit (although some solvers include back-tracking algorithms.)

This means that expressions such as a*log(a) can not be used if a might become zero. In this case it might be prudent to add a constraint a >= 1e-8 (or similar) to help the solver stay out of trouble.