The MOSEK Python optimizer API manual Version 7.0 (Revision 141)

68 CHAPTER 5. BASIC API TUTORIAL
• Task.putmaxnumanz. Estimate for the number of non-zeros in A.
• Task.putmaxnumqnz. Estimate for the number of non-zeros in the quadratic terms.
None of these functions change the problem, they only give hints to the eventual dimension of
the problem. If the problem ends up growing larger than this, the estimates are automatically
increased.
Do not mix put- and get- functions:
For instance, the functions Task.putacol and Task.getacol. MOSEK will queue put- commands
internally until a get- function is called. If every put- function call is followed by a getfunction
call, the queue will have to be flushed often, decreasing efficiency.
In general get- commands should not be called often during problem setup.
Use the LIFO principle when removing constraints and variables:
MOSEK can more efficiently remove constraints and variables with a high index than a small
index.
An alternative to removing a constraint or a variable is to fix it at 0, and set all relevant
coefficients to 0. Generally this will not have any impact on the optimization speed.
Add more constraints and variables than you need (now):
The cost of adding one constraint or one variable is about the same as adding many of them.
Therefore, it may be worthwhile to add many variables instead of one. Initially fix the unused
variable at zero, and then later unfix them as needed. Similarly, you can add multiple free
constraints and then use them as needed.
Use one environment (env) only:
If possible share the environment (env) between several tasks. For most applications you need
to create only a single env.
Do not remove basic variables:
When doing re-optimizations, instead of removing a basic variable it may be more efficient to
fix the variable at zero and then remove it when the problem is re-optimized and it has left the
basis. This makes it easier for MOSEK to restart the simplex optimizer.
5.12.1 API overhead
The Python interface is a thin wrapper around a native MOSEK library. The layer between the Python
application and the native MOSEK library is made as thin as possible to minimize the overhead from
function calls.
The methods in mosek.Env and mosek.Task are all written in C and resides in the module pymosek.
Each method converts the call parameter data structures (i.e. creates a complete copy of the data),
calls a MOSEK function and converts the returned values back into Python structures.
The follwing rules will often improve the performance of the MOSEK/Python API: