g_new = np.array([1.0, 1.5])
lb_new = np.array([0.0, -1.0])
ub_new = np.array([5.0, -0.5])
# Setting up QProblemB object.
example = QProblemB(2)
options = Options()
options.enableFlippingBounds = BooleanType.FALSE
options.initialStatusBounds = SubjectToStatus.INACTIVE
options.numRefinementSteps = 1
example.setOptions(options)
# Solve first QP.
nWSR = np.array([10])
example.init(H, g, lb, ub, nWSR)
print("\nnWSR = %d\n\n"%nWSR)
# Solve second QP.
nWSR = np.array([10])
example.hotstart(g_new, lb_new, ub_new, nWSR)
print("\nnWSR = %d\n\n"% nWSR)
# Get and print solution of second QP.
xOpt = np.zeros(2)
example.getPrimalSolution(xOpt)
print("\nxOpt = [ %e, %e ]; objVal = %e\n\n" %(xOpt[0], xOpt[1],
example.getObjVal()))
def test_example1b(self):
# Example for qpOASES main function using the QProblemB class.
#Setup data of first QP.
H = np.array([1.0, 0.0, 0.0, 0.5 ]).reshape((2,2))
g = np.array([1.5, 1.0 ])
lb = np.array([0.5, -2.0])
ub = np.array([5.0, 2.0 ])
# Setup data of second QP.
g_new = np.array([1.0, 1.5])
lb_new = np.array([0.0, -1.0])
ub_new = np.array([5.0, -0.5])
# Setting up QProblemB object.
qp = QProblemB(2)
options = Options()
options.enableFlippingBounds = BooleanType.FALSE
options.initialStatusBounds = SubjectToStatus.INACTIVE
options.numRefinementSteps = 1
options.printLevel = PrintLevel.NONE
qp.setOptions(options)
# Solve first QP.
nWSR = 10
qp.init(H, g, lb, ub, nWSR)
# Solve second QP.
nWSR = 10;
qp.hotstart(g_new, lb_new, ub_new, nWSR)
# Get and print solution of second QP.
xOpt_actual = np.zeros(2)
qp.getPrimalSolution(xOpt_actual)
xOpt_actual = np.asarray(xOpt_actual, dtype=float)
objVal_actual = qp.getObjVal()
objVal_actual = np.asarray(objVal_actual, dtype=float)
cmd = os.path.join(bin_path, "example1b")
p = Popen(cmd, shell=True, stdout=PIPE)
stdout, stderr = p.communicate()
stdout = str(stdout).replace('\\n', '\n')
stdout = stdout.replace("'", '')
print(stdout)
# get c++ solution from std
pattern = re.compile(r'xOpt\s*=\s*\[\s+(?P<xOpt>([0-9., e+-])*)\];')
match = pattern.search(stdout)
xOpt_expected = match.group('xOpt')
xOpt_expected = xOpt_expected.split(",")
xOpt_expected = np.asarray(xOpt_expected, dtype=float)
pattern = re.compile(r'objVal = (?P<objVal>[0-9-+e.]*)')
match = pattern.search(stdout)
objVal_expected = match.group('objVal')
objVal_expected = np.asarray(objVal_expected, dtype=float)
print("xOpt_actual =", xOpt_actual)
print("xOpt_expected =", xOpt_expected)
print("objVal_actual = ", objVal_actual)
print("objVal_expected = ", objVal_expected)
assert_almost_equal(xOpt_actual, xOpt_expected, decimal=7)
assert_almost_equal(objVal_actual, objVal_expected, decimal=7)
g_new = np.array([1.0, 1.5])
lb_new = np.array([0.0, -1.0])
ub_new = np.array([5.0, -0.5])
# Setting up QProblemB object.
example = QProblemB(2)
options = Options()
options.enableFlippingBounds = BooleanType.FALSE
options.initialStatusBounds = SubjectToStatus.INACTIVE
options.numRefinementSteps = 1
example.setOptions(options)
# Solve first QP.
nWSR = 10
example.init(H, g, lb, ub, nWSR)
print("\nnWSR = %d\n\n" % nWSR)
# Solve second QP.
nWSR = 10
example.hotstart(g_new, lb_new, ub_new, nWSR)
print("\nnWSR = %d\n\n" % nWSR)
# Get and print solution of second QP.
xOpt = np.zeros(2)
example.getPrimalSolution(xOpt)
print("\nxOpt = [ %e, %e ]; objVal = %e\n\n" %
(xOpt[0], xOpt[1], example.getObjVal()))
