def QPModel(self, addW=False):
A = self.A
c = self.c
s = CyClpSimplex()
x = s.addVariable('x', self.nCols)
if addW:
w = s.addVariable('w', self.nCols)
s += A * x >= 1
n = self.nCols
if not addW:
s += 0 <= x <= 1
else:
s += x + w == 1
s += 0 <= w <= 1
## s += -1 <= x <= 1
s.objective = c * x
if addW:
G = sparse.lil_matrix((2*n, 2*n))
for i in xrange(n/2, n): #xrange(n-1):
G[i, i] = 1
G[2*n-1, 2*n-1] = 10**-10
else:
G = sparse.lil_matrix((n, n))
for i in xrange(n/2, n): #xrange(n-1):
G[i, i] = 1
s.Hessian = G
return s
def generateQP(self):
m = self.m
n = self.n
s = CyClpSimplex()
iNonZero = set(random.randint(n, size=self.nnzPerCol))
iZero = [i for i in range(n) if i not in iNonZero]
x_star = np.matrix(np.zeros((n, 1)))
z_star = np.matrix(np.zeros((n, 1)))
for i in iNonZero:
x_star[i, 0] = 1
for i in iZero:
z_star[i, 0] = 0 if random.randint(2) else random.random()
G = getG(n)
A = getA(m, n, self.nnzPerCol)
y_star = np.matrix(random.random((m, 1)))
c = -(G * x_star - A.T * y_star - z_star)
obj = 0.5 * ((x_star.T * G) * x_star) + c.T * x_star
print(obj)
c = CyLPArray((c.T)[0])
b = CyLPArray(((A * x_star).T)[0])
b = np.squeeze(np.asarray(b))
x = s.addVariable('x', n)
s += A * x == b
s += x >= 0
c = CyLPArray(c)
s.objective = c * x
s.Hessian = G
self.model = s
return s
