# Use NumPy arrays for creating a 3-dimensional array of variables,
# then use it to create a mode.
#
# (C) Fair Isaac Corp., 1983-2020
from __future__ import print_function
import numpy as np
import xpress as xp
S1 = range(2)
S2 = range(3)
S3 = range(4)
m = xp.problem()
# Create a NumPy array of variables using the xp.npvar keyword. This
# is to ensure NumPy handles Xpress variable objects.
h = np.array([[[xp.var(vartype=xp.binary) for i in S1]
for j in S2] for k in S3], dtype=xp.npvar)
m.addVariable(h)
m.setObjective(h[0][0][0] * h[0][0][0] +
h[1][0][0] * h[0][0][0] +
h[1][0][0] * h[1][0][0] +
xp.Sum(h[i][j][k]
for i in S3 for j in S2 for k in S1))
cons00 = - h[0][0][0] * h[0][0][0] + \
xp.Sum(i * j * k * h[i][j][k]
for i in S3 for j in S2 for k in S1) >= 11
m.addConstraint(cons00)
m.solve()
# Get the matrix representation of the quadratic part of the single
# constraint
mstart1 = []
mclind1 = []
dqe1 = []
m.getqrowqmatrix(cons00, mstart1, mclind1, dqe1, 29,
h[0][0][0], h[3][2][1])
print("row 0:", mstart1, mclind1, dqe1)
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