import unittest

import LinearProgramming


class SimplexIterationTest(unittest.TestCase):

    def testSolutionVectorUnchanged(self):
        sm = LinearProgramming.SimplexIteration()
        sm.solution_vector = [1,2,3,4,5]
        self.assertTrue(sm.solution_vector == [1,2,3,4,5])


    def testBasicVariables(self):
        sm = LinearProgramming.SimplexIteration()
        sm.solution_vector = [0,1,0,1,0,1]
        sm.basic_variables = "x1,  x2, x3,x4,x5  "
        self.assertTrue("x1" in sm.basic_variables)
        self.assertTrue("x2" in sm.basic_variables)
        self.assertTrue("x3" in sm.basic_variables)
        self.assertTrue("x4" in sm.basic_variables)
        self.assertTrue("x5" in sm.basic_variables)


    def testNonBasicVariables(self):
        sm = LinearProgramming.SimplexIteration()
        sm.solution_vector = [1,0,0,4,5,6]
        sm.basic_indices = [0,3,4,5]
        self.assertTrue("x2" in sm.nonbasic_variables)
        self.assertTrue("x3" in sm.nonbasic_variables)


    def testBasisMatrix(self):
        sm = LinearProgramming.SimplexIteration()

        sm.solution_vector = [1, 0, 1, 1, 1, 0, 0, 1]
        sm.basic_variables = "x1,x3,x4,x5,x8"
        
        sm.constraint_matrix = [ [1, 1, 1, 0, 0, 0, 1, 0],
                                 [0, 0, 0, 1, 1, 1, 0, 1],
                                 [1, 0, 0, 1, 0, 0, 0, 0],
                                 [0, 1, 0, 0, 1, 0, 0, 0],
                                 [0, 0, 1, 0, 0, 1, 0, 0] ]

        expected_basis_matrix = [ [1, 1, 0, 0, 0],
                                  [0, 0, 1, 1, 1],
                                  [1, 0, 1, 0, 0],
                                  [0, 0, 0, 1, 0],
                                  [0, 1, 0, 0, 0] ]

        self.assertTrue(sm.basis_matrix() == expected_basis_matrix)


    def testOptimal(self):
        sm = LinearProgramming.SimplexIteration()
        sm.objective_coefficients = [ 5, 100, 30, 10, 20, 300, 0, 0 ]
        sm.solution_vector = [300, 0, 200, 100, 300, 0, 0, 200]
        sm.basic_variables = "x1,x3,x4,x5,x8"

        sm.constraint_matrix = [ [1, 1, 1, 0, 0, 0, 1, 0],
                                 [0, 0, 0, 1, 1, 1, 0, 1],
                                 [1, 0, 0, 1, 0, 0, 0, 0],
                                 [0, 1, 0, 0, 1, 0, 0, 0],
                                 [0, 0, 1, 0, 0, 1, 0, 0] ]

        self.assertTrue(sm.optimal)

        
    def testNonOptimal(self):
        sm = LinearProgramming.SimplexIteration()
        sm.objective_coefficients = [ 5, 100, 30, 10, 20, 300, 0, 0 ]
        sm.solution_vector = [0, 100, 200, 400, 200, 0, 200, 0]
        sm.basic_variables = "x2,x3,x4,x5,x7"

        sm.constraint_matrix = [ [1, 1, 1, 0, 0, 0, 1, 0],
                                 [0, 0, 0, 1, 1, 1, 0, 1],
                                 [1, 0, 0, 1, 0, 0, 0, 0],
                                 [0, 1, 0, 0, 1, 0, 0, 0],
                                 [0, 0, 1, 0, 0, 1, 0, 0] ]

        self.assertTrue(not sm.optimal)


def suite():
    suite = unittest.TestSuite()
    suite.addTest(unittest.makeSuite(SimplexIterationTest))
    return suite