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

5.2. LINEAR OPTIMIZATION 29
Optimization:
After the problem is set-up the task can be optimized by calling the function Task.optimize.
[ lo1.py ]
105 task.optimize()
Extracting the solution.
After optimizing the status of the solution is examined with a call to Task.getsolsta. If the
solution status is reported as solsta.optimal or solsta.near optimal the solution is extracted
in the lines below:
[ lo1.py ]
116 xx = zeros(numvar, float)
117 task.getxx(mosek.soltype.bas, # Request the basic solution.
118 xx)
The Task.getxx function obtains the solution. MOSEK may compute several solutions depending
on the optimizer employed. In this example the basic solution is requested by setting the
first argument to soltype.bas.
1 #
5.2.1.2 Source code for lo1
[ lo1.py ]
2 # Copyright: Copyright (c) MOSEK ApS, Denmark. All rights reserved.
3 #
4 # File: lo1.py
5 #
6 # Purpose: Demonstrates how to solve small linear
7 # optimization problem using the MOSEK Python API.
8 ##
9 from future import with statement
10
11 import sys
12 import mosek
13
14 # If numpy is installed, use that, otherwise use the
15 # Mosek’s array module.
16 try:
17 from numpy import array,zeros,ones
18 except ImportError:
19 from mosek.array import array, zeros, ones
20
21 # Since the value of infinity is ignored, we define it solely
22 # for symbolic purposes
23 inf = 0.0
24
25 # Define a stream printer to grab output from MOSEK
26 def streamprinter(text):
27 sys.stdout.write(text)
28 sys.stdout.flush()
29