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

104 CHAPTER 8. A CASE STUDY
73 task.putvarboundlist(range(offsett+0,offsett+n),n*[mosek.boundkey.fr],n*[-inf],n*[inf])
74 for j in range(0,n):
75 task.putvarname(offsett+j,"t[%d]" % (1+j))
76
77 task.appendcone(mosek.conetype.quad,0.0,[offsets] + range(offsett,offsett+n))
78 task.putconename(0,"stddev")
79
80 task.putobjsense(mosek.objsense.maximize)
81
82 # Turn all log output off.
83 task.putintparam(mosek.iparam.log,1)
84
85 # Dump the problem to a human readable OPF file.
86 #task.writedata("dump.opf")
87
88 task.optimize()
89
90 # Display the solution summary for quick inspection of results.
91 task.solutionsummary(mosek.streamtype.msg)
92
93 expret = 0.0
94 x = zeros(n,float)
95 task.getxxslice(mosek.soltype.itr,offsetx+0,offsetx+n,x)
96 for j in range(0,n):
97 expret += mu[j]*x[j]
98
99 stddev = zeros(1,float)
100 task.getxxslice(mosek.soltype.itr,offsets+0,offsets+1,stddev)
101
102 print("\nExpected return %e for gamma %e\n" % (expret,stddev[0]))
The above code produce the result
Interior-point solution summary
Problem status : PRIMAL AND DUAL FEASIBLE
Solution status : OPTIMAL
Primal. obj: 7.4766497707e-002 Viol. con: 2e-008 var: 0e+000 cones: 3e-009
Dual. obj: 7.4766522618e-002 Viol. con: 0e+000 var: 4e-008 cones: 0e+000
Expected return 7.476650e-02 for gamma 5.000000e-02
The source code should be self-explanatory but a few comments are nevertheless in place. In the lines
[ case portfolio 1.py ]
52 # Offset of variables into the API variable.
53 offsetx = 0
54 offsets = n
55 offsett = n+1
offsets into the MOSEK API variables are stored and those offsets are used later. The code
[ case portfolio 1.py ]
58 task.putclist(range(offsetx+0,offsetx+n),mu)
59 task.putaijlist(n*[0],range(offsetx+0,offsetx+n),n*[1.0])
60 for j in range(0,n):
61 task.putaijlist(n*[1+j],range(offsetx+0,offsetx+n),GT[j])
62