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

8.1. PORTFOLIO OPTIMIZATION 105
63 task.putvarboundlist(range(offsetx+0,offsetx+n),n*[mosek.boundkey.lo],n*[0.0],n*[inf])
64 for j in range(0,n):
65 task.putvarname(offsetx+j,"x[%d]" % (1+j))
sets up the data for x variables. For instance
[ case portfolio 1.py ]
58 task.putclist(range(offsetx+0,offsetx+n),mu)
inputs the objective coefficients for the x variables. Moreover, the code
[ case portfolio 1.py ]
64 for j in range(0,n):
65 task.putvarname(offsetx+j,"x[%d]" % (1+j))
assigns meaningful names to the API variables. This is not needed but it makes debugging easier.
8.1.2.3 Debugging tips
Implementing an optimization model in optimizer can be cumbersome and error-prone and it is very
easy to make mistakes. In order to check the implemented code for mistakes it is very useful to dump
the problem to a file in a human readable form for visual inspection. The line
86 #task.writedata("dump.opf")
[ case portfolio 1.py ]
does that and this will produce a file with the content
[comment]
Written by MOSEK version 7.0.0.86
Date 01-10-13
Time 08:15:47
[/comment]
[hints]
[hint NUMVAR] 7 [/hint]
[hint NUMCON] 4 [/hint]
[hint NUMANZ] 12 [/hint]
[hint NUMQNZ] 0 [/hint]
[hint NUMCONE] 1 [/hint]
[/hints]
[variables disallow new variables]
’x[1]’ ’x[2]’ ’x[3]’ s ’t[1]’
’t[2]’ ’t[3]’
[/variables]
[objective maximize]
1.073e-001 ’x[1]’ + 7.37e-002 ’x[2]’ + 6.270000000000001e-002 ’x[3]’
[/objective]
[constraints]
[con ’budget’]
’x[1]’ + ’x[2]’ + ’x[3]’ = 1e+000 [/con]