def test_check_for_existing_reaction_eliminates_identical_reactions_without_duplicate_flag(
self):
"""
Test that check_for_existing_reaction eliminates reactions with different templates and duplicate=false
"""
cerm = CoreEdgeReactionModel()
# make species' objects
spcA = Species().from_smiles('[H]')
spcB = Species().from_smiles('C=C[CH2]C')
spcC = Species().from_smiles('C=C=CC')
spcD = Species().from_smiles('[H][H]')
spcA.label = '[H]'
spcB.label = 'C=C[CH2]C'
spcC.label = 'C=C=CC'
spcD.label = '[H][H]'
spcB.generate_resonance_structures()
cerm.add_species_to_core(spcA)
cerm.add_species_to_core(spcB)
cerm.add_species_to_core(spcC)
cerm.add_species_to_core(spcD)
reaction_in_model = TemplateReaction(reactants=[spcA, spcB],
products=[spcC, spcD],
family='H_Abstraction',
template=['Csd', 'H'],
duplicate=False)
reaction_in_model.reactants.sort()
reaction_in_model.products.sort()
reaction_to_add = TemplateReaction(reactants=[spcA, spcB],
products=[spcC, spcD],
family='H_Abstraction',
template=['Cs12345', 'H'],
duplicate=False)
cerm.add_reaction_to_core(reaction_in_model)
cerm.register_reaction(reaction_in_model)
found, rxn = cerm.check_for_existing_reaction(reaction_to_add)
self.assertTrue(
found,
'check_for_existing_reaction failed to eliminate reactions without duplicate tag'
)
def test_check_for_existing_reaction_eliminates_identical_reactions(self):
"""
Test that check_for_existing_reaction catches identical reactions.
"""
cerm = CoreEdgeReactionModel()
# make species' objects
spcA = Species().from_smiles('[H]')
spcB = Species().from_smiles('C=C[CH2]C')
spcC = Species().from_smiles('C=C=CC')
spcD = Species().from_smiles('[H][H]')
spcA.label = '[H]'
spcB.label = 'C=C[CH2]C'
spcC.label = 'C=C=CC'
spcD.label = '[H][H]'
spcB.generate_resonance_structures()
cerm.add_species_to_core(spcA)
cerm.add_species_to_core(spcB)
cerm.add_species_to_core(spcC)
cerm.add_species_to_core(spcD)
reaction_in_model = TemplateReaction(reactants=[spcA, spcB],
products=[spcC, spcD],
family='H_Abstraction',
template=['Csd', 'H'])
reaction_in_model.reactants.sort()
reaction_in_model.products.sort()
reaction_to_add = TemplateReaction(reactants=[spcA, spcB],
products=[spcC, spcD],
family='H_Abstraction',
template=['Csd', 'H'])
cerm.add_reaction_to_core(reaction_in_model)
cerm.register_reaction(reaction_in_model)
found, rxn = cerm.check_for_existing_reaction(reaction_to_add)
self.assertTrue(
found,
'check_for_existing_reaction failed to identify existing reaction')
def test_thermo_filter_down(self):
"""
test that thermo_filter_down with maximum_edge_species = 1 reduces
the edge to one species
"""
cerm = CoreEdgeReactionModel()
spcs = [
Species().from_smiles('[OH]'),
Species().from_smiles('C'),
Species().from_smiles('[CH3]'),
Species().from_smiles('[CH2]'),
Species().from_smiles('O')
]
for spc in spcs:
cerm.make_new_species(spc, label=spc.molecule[0].to_smiles())
spc.label = spc.molecule[0].to_smiles()
thermo_dict = {
'[OH]':
NASA(polynomials=[
NASAPolynomial(coeffs=[
3.51457, 2.92787e-05, -5.32168e-07, 1.0195e-09,
-3.85947e-13, 3414.25, 2.10435
],
Tmin=(100, 'K'),
Tmax=(1145.75, 'K')),
NASAPolynomial(coeffs=[
3.07194, 0.000604014, -1.39775e-08, -2.13448e-11,
2.48067e-15, 3579.39, 4.578
],
Tmin=(1145.75, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(100, 'K'),
Tmax=(5000, 'K'),
E0=(28.3945, 'kJ/mol'),
Cp0=(29.1007, 'J/(mol*K)'),
CpInf=(37.4151, 'J/(mol*K)'),
label="""OH(D)""",
comment="""Thermo library: primaryThermoLibrary"""),
'C':
NASA(polynomials=[
NASAPolynomial(coeffs=[
4.20541, -0.00535551, 2.51121e-05, -2.1376e-08,
5.97513e-12, -10161.9, -0.921259
],
Tmin=(100, 'K'),
Tmax=(1084.13, 'K')),
NASAPolynomial(coeffs=[
0.908298, 0.011454, -4.57171e-06, 8.29185e-10,
-5.66309e-14, -9719.99, 13.9929
],
Tmin=(1084.13, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(100, 'K'),
Tmax=(5000, 'K'),
E0=(-84.435, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(108.088, 'J/(mol*K)'),
label="""CH4""",
comment="""Thermo library: primaryThermoLibrary"""),
'[CH3]':
NASA(polynomials=[
NASAPolynomial(coeffs=[
3.67359, 0.00201095, 5.73022e-06, -6.87117e-09,
2.54386e-12, 16445, 1.60456
],
Tmin=(200, 'K'),
Tmax=(1000, 'K')),
NASAPolynomial(coeffs=[
2.28572, 0.0072399, -2.98714e-06, 5.95685e-10,
-4.67154e-14, 16775.6, 8.48007
],
Tmin=(1000, 'K'),
Tmax=(3500, 'K'))
],
Tmin=(200, 'K'),
Tmax=(3500, 'K'),
E0=(136.42, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(83.1447, 'J/(mol*K)'),
label="""CH3""",
comment="""Thermo library: GRI-Mech3.0"""),
'[CH2]':
NASA(polynomials=[
NASAPolynomial(coeffs=[
4.01192, -0.000154978, 3.26298e-06, -2.40422e-09,
5.69497e-13, 45867.7, 0.533201
],
Tmin=(100, 'K'),
Tmax=(1104.62, 'K')),
NASAPolynomial(coeffs=[
3.14983, 0.00296674, -9.76056e-07, 1.54115e-10,
-9.50338e-15, 46058.1, 4.77808
],
Tmin=(1104.62, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(100, 'K'),
Tmax=(5000, 'K'),
E0=(381.37, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(58.2013, 'J/(mol*K)'),
label="""CH2(T)""",
comment="""Thermo library: primaryThermoLibrary"""),
'O':
NASA(polynomials=[
NASAPolynomial(coeffs=[
4.05764, -0.000787936, 2.90877e-06, -1.47519e-09,
2.12842e-13, -30281.6, -0.311364
],
Tmin=(100, 'K'),
Tmax=(1130.24, 'K')),
NASAPolynomial(coeffs=[
2.84325, 0.00275109, -7.81031e-07, 1.07244e-10,
-5.79392e-15, -29958.6, 5.91042
],
Tmin=(1130.24, 'K'),
Tmax=(5000, 'K'))
],
Tmin=(100, 'K'),
Tmax=(5000, 'K'),
E0=(-251.755, 'kJ/mol'),
Cp0=(33.2579, 'J/(mol*K)'),
CpInf=(58.2013, 'J/(mol*K)'),
label="""H2O""",
comment="""Thermo library: primaryThermoLibrary"""),
}
for spc in spcs[:3]:
cerm.add_species_to_core(spc)
reaction = TemplateReaction(reactants=[spcs[0], spcs[2]],
products=[spcs[-1], spcs[-2]],
degeneracy=1,
reversible=True,
family='H_Abstraction')
cerm.process_new_reactions(new_reactions=[reaction],
new_species=[]) # add CH2 and O to edge
for spc in cerm.core.species + cerm.edge.species:
spc.thermo = thermo_dict[
spc.molecule[0].to_smiles()] # assign thermo
cerm.set_thermodynamic_filtering_parameters(
Tmax=300.0,
thermo_tol_keep_spc_in_edge=1000.0,
min_core_size_for_prune=0,
maximum_edge_species=1,
reaction_systems=[])
difset = set([
x.molecule[0].to_smiles() for x in cerm.edge.species
]) - set([x.molecule[0].to_smiles() for x in cerm.core.species])
self.assertEquals(
len(difset),
2) # no change because toleranceThermoKeepSpeciesInEdge is high
cerm.thermo_filter_down(maximum_edge_species=1)
difset = set([
x.molecule[0].to_smiles() for x in cerm.edge.species
]) - set([x.molecule[0].to_smiles() for x in cerm.core.species])
self.assertEquals(
len(difset), 1
) # should be one because we thermo filtered down to one edge species