def runTest(self):
# Check for:
# ARGLALE = 'NLR2-AN-V-V'
# ROSENBR = 'SUR2-AN-2-0'
# BRATU2D = 'NOR2-MN-V-V'
# First, just find any problem
all_probs = pycutest.find_problems()
for p in ['ARGLALE', 'ROSENBR', 'BRATU2D']:
self.assertTrue(p in all_probs,
msg="All problems doesn't contain %s" % p)
# Now just find those with nonlinear objectives
nl = pycutest.find_problems(objective='N')
for p in ['ARGLALE', 'BRATU2D']:
self.assertTrue(p in nl,
msg="Nonlinear problems doesn't contain %s" % p)
# Simple objectives (unconstrained & linear)
simple_cons = pycutest.find_problems(constraints='UL')
for p in ['ARGLALE', 'ROSENBR']:
self.assertTrue(p in simple_cons,
msg="Nonlinear problems doesn't contain %s" % p)
# Regularity
reg = pycutest.find_problems(regular=True)
for p in ['ARGLALE', 'ROSENBR', 'BRATU2D']:
self.assertTrue(p in reg,
msg="Regular problems doesn't contain %s" % p)
# Degree
deg = pycutest.find_problems(degree=[2, 2])
for p in ['ARGLALE', 'ROSENBR', 'BRATU2D']:
self.assertTrue(p in deg,
msg="2nd order problems doesn't contain %s" % p)
# Origin
academic = pycutest.find_problems(origin='A')
for p in ['ARGLALE', 'ROSENBR']:
self.assertTrue(p in academic,
msg="Academic problems doesn't contain %s" % p)
# Internal
no_internal = pycutest.find_problems(internal=False)
for p in ['ARGLALE', 'ROSENBR', 'BRATU2D']:
self.assertTrue(p in no_internal,
msg="Non-internal problems doesn't contain %s" % p)
# Dimensions
twod = pycutest.find_problems(n=[2, 2])
for p in ['ROSENBR']:
self.assertTrue(p in twod,
msg="2D problems doesn't contain %s" % p)
# Variable dim
vardim = pycutest.find_problems(userN=True)
for p in ['ARGLALE', 'BRATU2D']:
self.assertTrue(p in vardim,
msg="Variable-dim problems doesn't contain %s" % p)
# Constraints
nocons = pycutest.find_problems(m=[0, 0])
for p in ['ROSENBR']:
self.assertTrue(p in nocons,
msg="Unconstrained problems doesn't contain %s" %
p)
# Variable dim
varcons = pycutest.find_problems(userM=True)
for p in ['ARGLALE', 'BRATU2D']:
self.assertTrue(
p in varcons,
msg="Variable-constraint problems doesn't contain %s" % p)
parser.add_argument('--N', type=int, default=0, help='Problem dimension')
args = parser.parse_args()
# define additional parameters
problemName = args.problemName
max_iter = 1000
tol = 1e-3
line_search = 'Wolfe'
interpolate = True
max_ls = 100
history_size = 10
out = True
# find all problems
if problemName == 'ALL':
problems = pycutest.find_problems(constraints='U', regular=True)
problems.remove('INDEF')
Ns = {}
elif problemName == 'L-BFGS':
problems = [
'ARWHEAD', 'BDQRTIC', 'BROYDN7D', 'CRAGGLVY', 'DIXMAANA', 'DIXMAANB',
'DIXMAANC', 'DIXMAAND', 'DIXMAANE', 'DIXMAANF', 'DIXMAANG', 'DIXMAANH',
'DIXMAANI', 'DIXMAANK', 'DIXMAANL', 'DQDRTIC', 'DQRTIC', 'DQRTIC',
'EIGENALS', 'EIGENBLS', 'EIGENCLS', 'ENGVAL1', 'FLETCHBV', 'FREUROTH',
'GENROSE', 'MOREBV', 'NONDIA', 'NONDQUAR', 'PENALTY1', 'PENALTY3',
'QUARTC', 'SINQUAD', 'SROSENBR', 'TQUARTIC', 'TRIDIA'
]
Ns = {
'ARWHEAD': 1000,
'BDQRTIC': 100,
'BROYDN7D': 1000,
def import_problems(self,
n_max,
objective='CLQSO',
constraints='U',
cutest=None,
path='.',
some_linear_equality=False):
"""Load the CUTEst problems matching the requirements. Not that some
requirements ask for the problem to be load before being rejected, such
as `some_equality=True`.
:param n_max: Upper bound on the dimension of the problems.
:param objective: String (substring of 'NCLQSO') specifying the type of
the objective function. The possible values for the objective
function are
- 'N' not to be defined,
- 'C' to be constant,
- 'L' to be linear,
- 'Q' to be quadratic,
- 'S' to be a sum of squares, and
- 'O' to be none of the above.
:param constraints: String (substring of 'UXBNLQO') specifying the type
of the constraints. The possible values for the constraints are
- 'U' not to be defined (unconstrained),
- 'X' to be fixed variables,
- 'B' to be bounds on the variables,
- 'N' to represent the adjacency matrix of a (linear) network,
- 'L' to be linear,
- 'Q' to be quadratic, and
- 'O' to be more general than any of the above alone.
:param cutest: List of problems to load or name of the file where the
problems are listed. If it is set, the parameters objective` and
`constraints` are not considered.
:param path: Path to the file where the problems are listed. It is used
only if `cutest` is set to a string.
:param some_linear_equality: Whether the problem should admits at least
one linear equality constraint.
"""
if cutest is None:
logging.info('CUTEST problem list provided.')
cutest = pycutest.find_problems(objective,
constraints,
n=[1, n_max])
elif isinstance(cutest, str):
path = Path(path).resolve(strict=True)
logging.info('Attempt to read %s' % str(path / cutest))
with open(path / cutest, 'r') as fo:
cutest = [c.strip(os.linesep) for c in fo.readlines()]
n_cutest = len(cutest)
# Attempt to load the selected CUTEst problems.
problems = []
for i_prob, prob in enumerate(sorted(cutest)):
logging.info('Import %d/%d: %s' % (i_prob + 1, n_cutest, prob))
try:
if pycutest.problem_properties(prob)['n'] is None:
# The dimensions of the problem are not fixed, and can be
# higher than n_max.
dimensions = self.get_sif_params(prob)
if dimensions.size > 0 and dimensions[0] <= n_max:
# The problem admits at least one possible value for the
# SIF parameter 'N' below n_max. We select the biggest
# one below n_max.
py_prob = pycutest.import_problem(
prob,
sifParams={
'N': np.max(dimensions[dimensions <= n_max]),
})
if py_prob.n > n_max:
# It seems that PyCUTEst sometimes return problems
# with incorrect dimension. We believe that it comes
# from the requirements of the CUTEst problems for
# the other SIF parameters. The exception will be
# caught in the `except` statement below.
raise RuntimeError()
else:
# None of the available SIF parameters for the given
# problem match the requirements. The exception will be
# caught in the `except` statement below.
raise RuntimeError()
else:
# The problem has a fixed dimension below n_max.
py_prob = pycutest.import_problem(prob)
# The problem is now loaded, and we can check the final
# requirements on its structure.
if some_linear_equality and \
not np.logical_and(py_prob.is_linear_cons,
py_prob.is_eq_cons).any():
logging.info('Failed: %s contains no linear equality '
'constraints.' % prob)
else:
problems.append(PCTProblem(py_prob))
logging.info('Success: %s (n=%d, m=%d) has been loaded' %
(prob, py_prob.n, py_prob.m))
except RuntimeError:
logging.info('Failed: Invalid dimensions of %s' % prob)
except (AttributeError, ModuleNotFoundError):
logging.info('Failed: PyCUTEst failed to load %s' % prob)
self.problems = problems