##
#  Copyright : Copyright (c) MOSEK ApS, Denmark. All rights reserved.
#
#  File :      milo1.py
#
#  Purpose :   Demonstrates how to solve a small mixed
#              integer linear optimization problem using the MOSEK Python API.
##
import sys
import mosek

# Since the actual value of Infinity is ignores, we define it solely
# for symbolic purposes:
inf = 0.0

# Define a stream printer to grab output from MOSEK
def streamprinter(text):
    sys.stdout.write(text)
    sys.stdout.flush()


def main():
    # Make a MOSEK environment
    with mosek.Env() as env:
        # Attach a printer to the environment
        env.set_Stream(mosek.streamtype.log, streamprinter)

        # Create a task
        with env.Task(0, 0) as task:
            # Attach a printer to the task
            task.set_Stream(mosek.streamtype.log, streamprinter)

            bkc = [mosek.boundkey.up, mosek.boundkey.lo]
            blc = [-inf, -4.0]
            buc = [250.0, inf]

            bkx = [mosek.boundkey.lo, mosek.boundkey.lo]
            blx = [0.0, 0.0]
            bux = [inf, inf]

            c = [1.0, 0.64]

            asub = [[0, 1], [0, 1]]
            aval = [[50.0, 3.0], [31.0, -2.0]]

            numvar = len(bkx)
            numcon = len(bkc)

            # Append 'numcon' empty constraints.
            # The constraints will initially have no bounds.
            task.appendcons(numcon)

            #Append 'numvar' variables.
            # The variables will initially be fixed at zero (x=0).
            task.appendvars(numvar)

            for j in range(numvar):
                # Set the linear term c_j in the objective.
                task.putcj(j, c[j])
                # Set the bounds on variable j
                # blx[j] <= x_j <= bux[j]
                task.putvarbound(j, bkx[j], blx[j], bux[j])
                # Input column j of A
                task.putacol(j,                  # Variable (column) index.
                             # Row index of non-zeros in column j.
                             asub[j],
                             aval[j])            # Non-zero Values of column j.

            task.putconboundlist(range(numcon), bkc, blc, buc)

            # Input the objective sense (minimize/maximize)
            task.putobjsense(mosek.objsense.maximize)

            # Define variables to be integers
            task.putvartypelist([0, 1],
                                [mosek.variabletype.type_int,
                                 mosek.variabletype.type_int])

            # Set max solution time
            task.putdouparam(mosek.dparam.mio_max_time, 60.0);

            # Optimize the task
            task.optimize()
            task.writedata("milo1.ptf")

            # Print a summary containing information
            # about the solution for debugging purposes
            task.solutionsummary(mosek.streamtype.msg)

            prosta = task.getprosta(mosek.soltype.itg)
            solsta = task.getsolsta(mosek.soltype.itg)

            # Output a solution         
            xx = task.getxx(mosek.soltype.itg)

            if solsta in [mosek.solsta.integer_optimal]:
                print("Optimal solution: %s" % xx)
            elif solsta == mosek.solsta.prim_feas:
                print("Feasible solution: %s" % xx)
            elif mosek.solsta.unknown:
                if prosta == mosek.prosta.prim_infeas_or_unbounded:
                    print("Problem status Infeasible or unbounded.\n")
                elif prosta == mosek.prosta.prim_infeas:
                    print("Problem status Infeasible.\n")
                elif prosta == mosek.prosta.unkown:
                    print("Problem status unkown.\n")
                else:
                    print("Other problem status.\n")
            else:
                print("Other solution status")


# call the main function
try:
    main()
except mosek.MosekException as msg:
    #print "ERROR: %s" % str(code)
    if msg is not None:
        print("\t%s" % msg)
        sys.exit(1)
except:
    import traceback
    traceback.print_exc()
    sys.exit(1)