# ___________________________________________________________________________
import os
import pyomo.common.unittest as unittest
import pyomo.environ as pyo
import math
from pyomo.contrib.pynumero.dependencies import (numpy as np, numpy_available,
scipy, scipy_available)
from pyomo.common.dependencies.scipy import sparse as spa
if not (numpy_available and scipy_available):
raise unittest.SkipTest("Pynumero needs scipy and numpy to run NLP tests")
from pyomo.contrib.pynumero.asl import AmplInterface
if not AmplInterface.available():
raise unittest.SkipTest(
"Pynumero needs the ASL extension to run CyIpoptSolver tests")
from pyomo.contrib.pynumero.algorithms.solvers.cyipopt_solver import (
CyIpoptSolver,
CyIpoptNLP,
cyipopt_available,
)
from pyomo.contrib.pynumero.interfaces.external_grey_box import ExternalGreyBoxModel, ExternalGreyBoxBlock
from pyomo.contrib.pynumero.interfaces.pyomo_nlp import PyomoGreyBoxNLP, PyomoNLP
from pyomo.contrib.pynumero.interfaces.pyomo_grey_box_nlp import PyomoNLPWithGreyBoxBlocks
from pyomo.contrib.pynumero.interfaces.tests.compare_utils import check_vectors_specific_order, check_sparse_matrix_specific_order
import pyutilib.th as unittest
import pyomo.environ as pe
from pyomo.opt import check_optimal_termination
from pyomo.common.dependencies import attempt_import
np, numpy_available = attempt_import('numpy',
'inverse_reduced_hessian numpy',
minimum_version='1.13.0')
scipy, scipy_available = attempt_import(
'scipy', 'inverse_reduced_hessian requires scipy')
if numpy_available:
from pyomo.contrib.pynumero.asl import AmplInterface
asl_available = AmplInterface.available()
else:
asl_available = False
if not (numpy_available and scipy_available and asl_available):
raise unittest.SkipTest(
'inverse_reduced_hessian tests require numpy, scipy, and asl')
from pyomo.common.dependencies import (pandas as pd, pandas_available)
import pyomo.environ as pe
ipopt_solver = pe.SolverFactory('ipopt')
if not ipopt_solver.available(exception_flag=False):
raise unittest.SkipTest('ipopt is not available')
numdiff_available = True
try:
import numdifftools as nd
except:
numdiff_available = False
from pyomo.contrib.incidence_analysis.tests.models_for_testing import (
make_gas_expansion_model,
make_degenerate_solid_phase_model,
)
if scipy_available:
from pyomo.contrib.pynumero.interfaces.pyomo_nlp import PyomoNLP
if networkx_available:
from networkx.algorithms.bipartite.matrix import from_biadjacency_matrix
from pyomo.contrib.pynumero.asl import AmplInterface
import pyomo.common.unittest as unittest
@unittest.skipUnless(networkx_available, "networkx is not available.")
@unittest.skipUnless(scipy_available, "scipy is not available.")
@unittest.skipUnless(AmplInterface.available(),
"pynumero_ASL is not available")
class TestGasExpansionNumericIncidenceMatrix(unittest.TestCase):
"""
This class tests the get_numeric_incidence_matrix function on
the gas expansion model.
"""
def test_incidence_matrix(self):
N = 5
model = make_gas_expansion_model(N)
all_vars = list(model.component_data_objects(pyo.Var))
all_cons = list(model.component_data_objects(pyo.Constraint))
imat = get_numeric_incidence_matrix(all_vars, all_cons)
n_var = 4 * (N + 1)
n_con = 4 * N + 1
self.assertEqual(imat.shape, (n_con, n_var))
