def test_elementary(self):
r = ct.ElementaryReaction({'O':1, 'H2':1}, {'H':1, 'OH':1})
r.rate = ct.Arrhenius(3.87e1, 2.7, 6260*1000*4.184)
gas2 = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=self.species, reactions=[r])
gas2.TPX = self.gas.TPX
self.assertNear(gas2.forward_rate_constants[0],
self.gas.forward_rate_constants[2])
self.assertNear(gas2.net_rates_of_progress[0],
self.gas.net_rates_of_progress[2])
def test_negative_A(self):
species = ct.Species.listFromFile('gri30.cti')
r = ct.ElementaryReaction('NH:1, NO:1', 'N2O:1, H:1')
r.rate = ct.Arrhenius(-2.16e13, -0.23, 0)
self.assertFalse(r.allow_negative_pre_exponential_factor)
with self.assertRaises(Exception):
gas = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=species, reactions=[r])
r.allow_negative_pre_exponential_factor = True
gas = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
species=species, reactions=[r])
def test_modify_invalid(self):
# different reaction type
tbr = self.gas.reaction(0)
R2 = ct.ElementaryReaction(tbr.reactants, tbr.products)
R2.rate = tbr.rate
with self.assertRaises(ct.CanteraError):
self.gas.modify_reaction(0, R2)
# different reactants
R = self.gas.reaction(7)
with self.assertRaises(ct.CanteraError):
self.gas.modify_reaction(23, R)
# different products
R = self.gas.reaction(14)
with self.assertRaises(ct.CanteraError):
self.gas.modify_reaction(15, R)
def remove(seed, num, exclude):
np.random.seed(seed)
reactions = gas.reactions()
removed = []
rcandidates = range(0, len(reactions))
rcandidates = [item for item in rcandidates if item not in exclude]
removed = np.random.choice(rcandidates, size=num, replace=False)
for ind in removed:
if (gas.reaction_type(ind) == 1):
newreac = ct.ElementaryReaction(reactants=reactions[ind].reactants,
products=reactions[ind].products)
gas.modify_reaction(ind, newreac)
if (gas.reaction_type(ind) == 2):
newreac = ct.ThreeBodyReaction(reactants=reactions[ind].reactants,
products=reactions[ind].products)
gas.modify_reaction(ind, newreac)
if (gas.reaction_type(ind) == 4):
newreac = ct.FalloffReaction(reactants=reactions[ind].reactants,
products=reactions[ind].products)
gas.modify_reaction(ind, newreac)
return removed
constants for reaction 2 and reaction 3 to show that even two reactions that have the
same Blowers-Masel parameters can have different forward rate constants.
The first plot generated shows how the rate constant changes with respect to temperature
for elementary and Blower-Masel reactions. The second plot shows the activation energy
change of a Blowers-Masel reaction with respect to the delta enthalpy of the reaction.
Requires: cantera >= 2.6.0, matplotlib >= 2.0
"""
import cantera as ct
import numpy as np
import matplotlib.pyplot as plt
#Create an elementary reaction O+H2<=>H+OH
r1 = ct.ElementaryReaction({'O': 1, 'H2': 1}, {'H': 1, 'OH': 1})
r1.rate = ct.Arrhenius(3.87e1, 2.7, 6260 * 1000 * 4.184)
#Create a Blowers-Masel reaction O+H2<=>H+OH
r2 = ct.BlowersMaselReaction({'O': 1, 'H2': 1}, {'H': 1, 'OH': 1})
r2.rate = ct.BlowersMasel(3.87e1, 2.7, 6260 * 1000 * 4.184, 1e9)
#Create a Blowers-Masel reaction with same parameters with r2
#reaction equation is H+CH4<=>CH3+H2
r3 = ct.BlowersMaselReaction({'H': 1, 'CH4': 1}, {'CH3': 1, 'H2': 1})
r3.rate = ct.BlowersMasel(3.87e1, 2.7, 6260 * 1000 * 4.184, 1e9)
gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=ct.Solution('gri30.yaml').species(),
reactions=[r1, r2, r3])
def perturb_parameter_thisisthecomplicatedonethatdoesntwork(
self, parameter, new_value):
param_info = self.model_parameter_info[parameter]
reaction_number = param_info['reaction_number']
parameter_type = param_info['parameter_type']
print(parameter)
print(param_info)
reaction = self.gas.reaction(reaction_number)
print(reaction.rate)
rate = None
efficiencies = None
reactants = reaction.reactant_string
products = reaction.product_string
rtype = reaction.reaction_type
pressurestring = 'pressure'
HasFalloff = False
if pressurestring in parameter_type:
HasFalloff = True
if HasFalloff:
highrate = reaction.high_rate
lowrate = reaction.low_rate
if rtype == 4:
newreaction = ct.FalloffReaction(reactants=reactants,
products=products)
if rtype == 8:
newreaction = ct.ChemicallyActivatedReaction(
reactants=reactants, products=products)
else:
rate = reaction.rate
if rtype == 2:
newreaction = ct.ThreeBodyReaction(reactants=reactants,
products=products)
else:
newreaction = ct.ElementaryReaction(reactants=reactants,
products=products)
if parameter_type == 'A_factor':
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'Energy':
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
if parameter_type == 'High_pressure_A':
rate = highrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.high_rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'High_pressure_E':
rate = highrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.high_rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
if parameter_type == 'Low_pressure_A':
rate = lowrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_A = new_value
newreaction.low_rate = ct.Arrhenius(A=new_A, b=old_b, E=old_E)
if parameter_type == 'Low_pressure_E':
rate = lowrate
old_A = rate.pre_exponential_factor
old_b = rate.temperature_exponent
old_E = rate.activation_energy
new_E = new_value
newreaction.low_rate = ct.Arrhenius(A=old_A, b=old_b, E=new_E)
self.gas.modify_reaction(reaction_number, newreaction)
if parameter_type == 'Efficiency':
efficiencies = copy.deepcopy(reaction.efficiencies)
species = param_info['species']
efficiencies[species] = new_value
reaction.efficiencies = efficiencies
return
def residual(eta, k0, observations, measure_ind, tmaxes, temperatures,
pressures, initials, maxes, yields):
rstart = timeit.default_timer()
ret = 0
reactions = gas.reaction_equations()
k = k0 * 10**eta
if (gas.reaction_type(measure_ind) == 1):
newrate = ct.ElementaryReaction(gas.reactions()[measure_ind].reactants,
gas.reactions()[measure_ind].products)
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 2):
newrate = ct.ThreeBodyReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 4):
newrate = ct.FalloffReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.falloff = gas.reactions()[measure_ind].falloff
newrate.low_rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].low_rate.temperature_exponent,
gas.reactions()[measure_ind].low_rate.temperature_exponent,
gas.reactions()[measure_ind].low_rate.activation_energy)
newrate.high_rate = gas.reactions()[measure_ind].high_rate
gas.modify_reaction(measure_ind, newrate)
sys.stdout.flush()
for i in range(0, nmeasure):
states = runsim_nosense(tmaxes[i], temperatures[i], pressures[i],
initials[i])
for n in maxes:
lst1 = observations[i].X[:, n]
lst2 = states.X[:, n]
ind1 = np.array(np.where(np.sign(np.diff(lst1)) == -1))[0, 0]
if np.any(np.sign(np.diff(lst2)) == -1):
ind2 = np.array(np.where(np.sign(np.diff(lst2)) == -1))[0, 0]
else:
ind2 = len(lst2) - 1
ret += ((1.0 * ind2 / ind1 - 1)**2 +
(lst2[ind2] / lst1[ind1] - 1)**2) / nmeasure
if (outflag == 1):
print(temperatures[i], tmaxes[i], pressures[i] / ct.one_atm,
(1.0 * ind2 / ind1 - 1), (lst2[ind2] / lst1[ind1] - 1))
sys.stdout.flush()
for n in yields:
lst1 = observations[i].X[:, n]
lst2 = states.X[:, n]
ret += ((lst2[-1] / lst1[-1] - 1)**2) / nmeasure
if (outflag == 1):
print(temperatures[i], tmaxes[i], pressures[i] / ct.one_atm,
(lst2[-1] / lst1[-1] - 1))
sys.stdout.flush()
if (outflag == 1):
rstop = timeit.default_timer()
print('iter time: %f' % (rstop - rstart))
print('residual: ', ret)
print('x: ', eta)
sys.stdout.flush()
return np.sqrt(ret)
sensnorm,
k / k0,
result.fun,
*removed,
sep=' ',
file=f)
f.close()
if (outflag == 1):
print(result)
sys.stdout.flush()
reactions = gas.reaction_equations()
if (gas.reaction_type(measure_ind) == 1):
newrate = ct.ElementaryReaction(
gas.reactions()[measure_ind].reactants,
gas.reactions()[measure_ind].products)
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
gas.modify_reaction(measure_ind, newrate)
if (gas.reaction_type(measure_ind) == 2):
newrate = ct.ThreeBodyReaction(
reactants=gas.reactions()[measure_ind].reactants,
products=gas.reactions()[measure_ind].products)
newrate.efficiencies = gas.reactions()[measure_ind].efficiencies
newrate.rate = ct.Arrhenius(
k,
gas.reactions()[measure_ind].rate.temperature_exponent,
gas.reactions()[measure_ind].rate.activation_energy)
[300.00, 1000.00],
[2.08692170E+00, 1.33149650E-01, -8.11574520E-05,
2.94092860E-08, -6.51952130E-12, -3.59128140E+04,
2.73552890E+01]
),
NASA(
[1000.00, 5000.00],
[2.48802010E+01, 7.82500480E-02, -3.15509730E-05,
5.78789000E-09, -3.98279680E-13, -4.31106840E+04,
-9.36552550E+01]
)
),
)
reaction(
equation='A => B',
kf=Arrhenius(A=52499925000.0, b=1.5, E=40900.0),
)
"""
gas = ct.Solution(source=cti_str)
gas.TP = 1000, 101325
print(gas.reactions()[0].rate(1000))
print(gas.forward_rate_constants)
r = ct.ElementaryReaction({'A': 1}, {'B': 1})
r.rate = ct.Arrhenius(3.87e1, 2.7, 6260 * 1000 * 4.184)
gas.modify_reaction(0, r)
print(gas.reactions()[0].rate(1000))
print(gas.forward_rate_constants)
def _build_cantera_solution(cls, gdata):
p_ref = gdata['ref_pressure']
species_list = list()
for s in gdata['species']:
spec = gdata['species'][s]
ctspec = ct.Species(
s, ','.join(
[f'{k}:{spec["atom_map"][k]}' for k in spec['atom_map']]))
if spec['cp'][0] == 'constant':
Tmin, Tmax, T0, h0, s0, cp = spec['cp'][1:]
ctspec.thermo = ct.ConstantCp(Tmin, Tmax, p_ref,
list([T0, h0, s0, cp]))
elif spec['cp'][0] == 'NASA7':
Tmin, Tmid, Tmax, low_coeffs, high_coeffs = spec['cp'][1:]
coeffs = [Tmid] + high_coeffs + low_coeffs
ctspec.thermo = ct.NasaPoly2(Tmin, Tmax, p_ref, coeffs)
species_list.append(ctspec)
reaction_list = list()
for rxn in gdata['reactions']:
type, reactants_stoich, products_stoich, reversible = rxn[:4]
fwd_pre_exp_value, fwd_temp_exponent, fwd_act_energy = rxn[4:7]
fwd_rate = ct.Arrhenius(fwd_pre_exp_value, fwd_temp_exponent,
fwd_act_energy)
if type == 'simple' or type == 'simple-special':
ctrxn = ct.ElementaryReaction(reactants_stoich,
products_stoich)
ctrxn.rate = fwd_rate
elif type == 'three-body' or type == 'three-body-special':
ctrxn = ct.ThreeBodyReaction(reactants_stoich, products_stoich)
ctrxn.rate = fwd_rate
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
elif type == 'Lindemann' or type == 'Lindemann-special':
ctrxn = ct.FalloffReaction(reactants_stoich, products_stoich)
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
flf_pre_exp_value, flf_temp_exponent, flf_act_energy = rxn[
9:12]
ctrxn.high_rate = fwd_rate
ctrxn.low_rate = ct.Arrhenius(flf_pre_exp_value,
flf_temp_exponent,
flf_act_energy)
ctrxn.falloff = ct.Falloff()
elif type == 'Troe' or type == 'Troe-special':
ctrxn = ct.FalloffReaction(reactants_stoich, products_stoich)
ctrxn.efficiencies = rxn[7]
ctrxn.default_efficiency = rxn[8]
flf_pre_exp_value, flf_temp_exponent, flf_act_energy = rxn[
9:12]
troe_params = rxn[12]
ctrxn.high_rate = fwd_rate
ctrxn.low_rate = ct.Arrhenius(flf_pre_exp_value,
flf_temp_exponent,
flf_act_energy)
if len(troe_params) == 4 and abs(troe_params[3]) < 1e-300:
ctrxn.falloff = ct.TroeFalloff(troe_params[:3])
else:
ctrxn.falloff = ct.TroeFalloff(troe_params)
if 'special' in type:
ctrxn.orders = rxn[-1]
ctrxn.reversible = reversible
reaction_list.append(ctrxn)
return ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species_list,
reactions=reaction_list)
def set_mechanism(self, mech_dict, species_dict={}, bnds=[]):
def get_Arrhenius_parameters(entry):
A = entry['pre_exponential_factor']
b = entry['temperature_exponent']
Ea = entry['activation_energy']
return A, b, Ea
if len(species_dict) == 0:
species = self.gas.species()
else:
species = []
for n in range(len(species_dict)):
s_dict = species_dict[n]
s = ct.Species(name=s_dict['name'],
composition=s_dict['composition'],
charge=s_dict['charge'],
size=s_dict['size'])
thermo = s_dict['type'](s_dict['T_low'], s_dict['T_high'],
s_dict['P_ref'], s_dict['coeffs'])
s.thermo = thermo
species.append(s)
# Set kinetics data
rxns = []
for rxnIdx in range(len(mech_dict)):
if 'ElementaryReaction' == mech_dict[rxnIdx]['rxnType']:
rxn = ct.ElementaryReaction(mech_dict[rxnIdx]['reactants'],
mech_dict[rxnIdx]['products'])
rxn.allow_negative_pre_exponential_factor = True
A, b, Ea = get_Arrhenius_parameters(
mech_dict[rxnIdx]['rxnCoeffs'][0])
rxn.rate = ct.Arrhenius(A, b, Ea)
elif 'ThreeBodyReaction' == mech_dict[rxnIdx]['rxnType']:
rxn = ct.ThreeBodyReaction(mech_dict[rxnIdx]['reactants'],
mech_dict[rxnIdx]['products'])
A, b, Ea = get_Arrhenius_parameters(
mech_dict[rxnIdx]['rxnCoeffs'][0])
rxn.rate = ct.Arrhenius(A, b, Ea)
rxn.efficiencies = mech_dict[rxnIdx]['rxnCoeffs'][0][
'efficiencies']
elif 'PlogReaction' == mech_dict[rxnIdx]['rxnType']:
rxn = ct.PlogReaction(mech_dict[rxnIdx]['reactants'],
mech_dict[rxnIdx]['products'])
rates = []
for plog in mech_dict[rxnIdx]['rxnCoeffs']:
pressure = plog['Pressure']
A, b, Ea = get_Arrhenius_parameters(plog)
rates.append((pressure, ct.Arrhenius(A, b, Ea)))
rxn.rates = rates
elif 'FalloffReaction' == mech_dict[rxnIdx]['rxnType']:
rxn = ct.FalloffReaction(mech_dict[rxnIdx]['reactants'],
mech_dict[rxnIdx]['products'])
# high pressure limit
A, b, Ea = get_Arrhenius_parameters(
mech_dict[rxnIdx]['rxnCoeffs']['high_rate'])
rxn.high_rate = ct.Arrhenius(A, b, Ea)
# low pressure limit
A, b, Ea = get_Arrhenius_parameters(
mech_dict[rxnIdx]['rxnCoeffs']['low_rate'])
rxn.low_rate = ct.Arrhenius(A, b, Ea)
# falloff parameters
if mech_dict[rxnIdx]['rxnCoeffs']['falloff_type'] == 'Troe':
falloff_param = mech_dict[rxnIdx]['rxnCoeffs'][
'falloff_parameters']
if falloff_param[-1] == 0.0:
falloff_param = falloff_param[0:-1]
rxn.falloff = ct.TroeFalloff(falloff_param)
else:
rxn.falloff = ct.SriFalloff(
mech_dict[rxnIdx]['rxnCoeffs']['falloff_parameters'])
rxn.efficiencies = mech_dict[rxnIdx]['rxnCoeffs'][
'efficiencies']
elif 'ChebyshevReaction' == mech_dict[rxnIdx]['rxnType']:
rxn = ct.ChebyshevReaction(mech_dict[rxnIdx]['reactants'],
mech_dict[rxnIdx]['products'])
rxn.set_parameters(Tmin=mech_dict['Tmin'],
Tmax=mech_dict['Tmax'],
Pmin=mech_dict['Pmin'],
Pmax=mech_dict['Pmax'],
coeffs=mech_dict['coeffs'])
rxn.duplicate = mech_dict[rxnIdx]['duplicate']
rxn.reversible = mech_dict[rxnIdx]['reversible']
rxn.allow_negative_orders = True
rxn.allow_nonreactant_orders = True
rxns.append(rxn)
self.gas = ct.Solution(thermo='IdealGas',
kinetics='GasKinetics',
species=species,
reactions=rxns)
self.set_rate_expression_coeffs(bnds) # set copy of coeffs
self.set_thermo_expression_coeffs() # set copy of thermo coeffs
def run(gas, interval, num_states, work_dir, repeats=10):
def arrhenius(T, A, b, Ea, print_stats=False):
vals = A * np.power(T, b) * np.exp(-Ea / (ct.gas_constant * T))
if print_stats:
print(A, b, Ea, np.max(np.abs(vals - kf) / kf))
return vals
# first, convert all reactions to a single rate form
reacs = gas.reactions()[:]
for i, reac in enumerate(reacs):
if isinstance(reac, ct.ChemicallyActivatedReaction):
reacs[i] = ct.ElementaryReaction(reac.reactants, reac.products)
reacs[i].rate = reac.high_rate
elif isinstance(reac, ct.FalloffReaction):
reacs[i] = ct.ElementaryReaction(reac.reactants, reac.products)
reacs[i].rate = reac.high_rate
elif isinstance(reac, ct.ThreeBodyReaction):
reacs[i] = ct.ElementaryReaction(reac.reactants, reac.products)
reacs[i].rate = reac.rate
elif isinstance(reac, ct.PlogReaction):
reacs[i] = ct.ElementaryReaction(reac.reactants, reac.products)
reacs[i].rate = reac.rates[-1][1]
elif isinstance(reac, ct.ChebyshevReaction):
# fit _something_ to it at a 10 bar, for 600-2200K
T = np.linspace(600, 2200, num=1000)
kf = np.zeros_like(T)
for j in range(T.size):
kf[j] = reac(T[j], 10 * 10*1e5)
A = 1e10
b = 1
Ea = 1200 * ct.gas_constant
(A, b, Ea), _ = curve_fit(
arrhenius, T, kf,
p0=[A, b, Ea],
bounds=[(0, -2, 0), (np.inf, 5, np.inf)],
maxfev=1e6,
xtol=1e-15)
if False:
plt.plot(T, kf, color='b', linestyle='-', label='cheb')
plt.plot(T, arrhenius(T, A, b, Ea), color='r', linestyle='--',
label='fit')
plt.legend(loc=0)
plt.show()
reacs[i] = ct.ElementaryReaction(reac.reactants, reac.products)
reacs[i].rate = ct.Arrhenius(A, b, Ea)
# set all to reversible
reacs[i].reversible = True
# and convert gas
gas = ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
reactions=reacs,
species=gas.species())
# next, order the reactions by the number of distinct species
def get_reac_and_spec_maps(mygas):
# first, create rxn->species maps
reac_nu = mygas.reactant_stoich_coeffs()
prod_nu = mygas.product_stoich_coeffs()
# species -> rxn mappings
spec_masks = np.zeros((mygas.n_species, mygas.n_reactions),
dtype=np.bool)
# the reaction -> species mappings
reac_masks = []
for i, reac in enumerate(mygas.reactions()):
for spec in set(list(reac.reactants.keys()) + list(
reac.products.keys())):
j = mygas.species_index(spec)
if prod_nu[j, i] - reac_nu[j, i]:
# non-zero species
spec_masks[j, i] = True
reac_masks.append(np.where(spec_masks[:, i])[0])
# convert to flat, fixed size array
copy = np.array(reac_masks, copy=True)
max_size = np.max([x.size for x in reac_masks])
reac_masks = np.full((len(reac_masks), max_size), -1)
for i, mask in enumerate(copy):
reac_masks[i, :mask.size] = mask[:]
return spec_masks, reac_masks
# ensure we didn't remove any species
spec_masks, reac_masks = get_reac_and_spec_maps(gas)
converted_spec_count = np.where(~np.sum(spec_masks, axis=1))[0].size
assert converted_spec_count == gas.n_species
def species_to_rxn_count(reac_list=slice(None)):
"""
The number of reactions each species is in
"""
return np.sum(spec_masks[:, reac_list], axis=1)
def simple(specs, spec_counts):
"""
Returns 0 if any species in the reaction is unique to that reaction
otherwise mean of the number of reactions per species in the reaction
"""
specs = specs[np.where(specs >= 0)]
if np.any(spec_counts[specs] == 1):
return 0
return np.mean(spec_counts[specs])
def minh(specs, spec_counts):
"""
The minimum number of reactions any species in the reaction is in
"""
specs = specs[np.where(specs >= 0)]
minh = np.min(spec_counts[specs])
return 0 if minh == 1 else minh
def rxn_scores(heuristic, reac_list=slice(None)):
"""
Returns a score from 0--1, where 1 indicates that the reactions is a
good removal candidate and 0 a bad candidate
Heuristics correspond to local methods
"""
reac_list = np.arange(gas.n_reactions)[reac_list]
s2r = species_to_rxn_count(reac_list)
scores = np.apply_along_axis(heuristic, 1, reac_masks[reac_list], s2r)
return scores
def get_next_removed(heuristic, reac_list=slice(None)):
"""
Get the index of the next reaction to remove from the current reac_list
using the given heuristic
"""
scores = rxn_scores(heuristic, reac_list)
amax = np.argmax(scores)
if scores[amax] == 0:
return -1
return reac_list[amax]
def active_reactions(reac_list, return_active=False):
"""
Returns the number of active reactions in the reac_list
If return_active is True, return the list of active reactions
"""
alist = np.where(reac_list >= 0)[0]
if return_active:
return alist
return alist.size
saved_reaction_lists = []
reac_list = np.arange(gas.n_reactions)
saved_reaction_lists.append(active_reactions(reac_list, True))
while True:
remove_at = get_next_removed(minh, reac_list=np.where(
reac_list >= 0)[0])
if remove_at == -1:
break
reac_list[remove_at] = -1
if (active_reactions(reac_list) <= active_reactions(
saved_reaction_lists[-1]) - interval):
# save list
saved_reaction_lists.append(active_reactions(reac_list, True))
# get final reaction list and save
reac_list = active_reactions(reac_list, True)
saved_reaction_lists.append(reac_list)
def gas_from_reac_list(reac_list):
reacs = gas.reactions()[:]
reacs = [reacs[i] for i in reac_list]
return ct.Solution(thermo='IdealGas', kinetics='GasKinetics',
reactions=reacs,
species=gas.species())
# remap, and ensure the number of removed species is not less than
# previously
newgas = gas_from_reac_list(reac_list)
smap_final, _ = get_reac_and_spec_maps(newgas)
scount_final = np.where(~np.sum(smap_final, axis=1))[0].size
assert scount_final == converted_spec_count
print('Final mechanism size: {} reactions, {} species'.format(
newgas.n_reactions, scount_final))
vecsize = 8
platform = 'intel'
split_rate_kernels = False
lang = 'opencl'
rate_spec = 'hybrid'
num_cores = 1
order = 'C'
def get_filename(wide=False):
"""
emulate pyjac's naming scheme
"""
desc = 'spec'
vsize = vecsize if wide else '1'
vectype = 'w' if wide else 'par'
platform = 'intel'
split = 'split' if split_rate_kernels else 'single'
conp = 'conp'
return '{}_{}_{}_{}_{}_{}_{}_{}_{}_{}'.format(
desc, lang, vsize, order,
vectype, platform, rate_spec,
split, num_cores, conp) + '.txt'
def check_file(file):
if not os.path.exists(file):
return repeats
with open(file, 'r') as f:
lines = f.readlines()
import re
todo = repeats
for line in lines:
line = line.split(',')
if len(line) > 1 and sum(
1 if re.search(r'(?:\d+(?:\.\d+e[+-]\d+))', l) else 0
for l in line) == 4:
# four doubles -> good line
todo -= 1
return todo
build = os.path.join(path, 'out')
obj = os.path.join(path, 'obj')
lib = os.path.join(path, 'lib')
for wide in [True, False]:
vsize = vecsize if wide else None
# now, go through the various generated reactions lists and run
# the test on each
for reac_list in saved_reaction_lists:
outname = get_filename(wide)
todo = check_file(outname)
# clean
clean_dir(build, remove_dir=False)
clean_dir(obj, remove_dir=False)
clean_dir(lib, remove_dir=False)
subdir = os.path.join(work_dir, str(active_reactions(reac_list)))
create_dir(subdir)
# generate the source rate evaluation
rgas = gas_from_reac_list(reac_list)
create_jacobian('opencl', gas=rgas, vector_size=vsize,
wide=wide, build_path=build,
rate_specialization=rate_spec,
split_rate_kernels=split_rate_kernels,
data_filename=os.path.abspath(
os.path.join(work_dir, 'data.bin')),
data_order=order,
platform=platform,
skip_jac=True)
# first create the executable (via libgen)
tester = generate_library(lang, build, obj_dir=obj, out_dir=lib,
shared=True,
btype=build_type.species_rates,
as_executable=True)
# and do runs
with open(os.path.join(subdir, outname), 'a+') as file:
for i in range(todo):
print(i, "/", todo)
subprocess.check_call([os.path.join(lib, tester),
str(num_states), str(1)],
stdout=file)
def toCantera(self, speciesList=None, useChemkinIdentifier = False):
"""
Converts the RMG Reaction object to a Cantera Reaction object
with the appropriate reaction class.
If useChemkinIdentifier is set to False, the species label is used
instead. Be sure that species' labels are unique when setting it False.
"""
from rmgpy.kinetics import Arrhenius, ArrheniusEP, MultiArrhenius, PDepArrhenius, MultiPDepArrhenius, Chebyshev, ThirdBody, Lindemann, Troe
import cantera as ct
if speciesList is None:
speciesList = []
# Create the dictionaries containing species strings and their stoichiometries
# for initializing the cantera reaction object
ctReactants = {}
for reactant in self.reactants:
if useChemkinIdentifier:
reactantName = reactant.toChemkin()
else:
reactantName = reactant.label
if reactantName in ctReactants:
ctReactants[reactantName] += 1
else:
ctReactants[reactantName] = 1
ctProducts = {}
for product in self.products:
if useChemkinIdentifier:
productName = product.toChemkin()
else:
productName = product.label
if productName in ctProducts:
ctProducts[productName] += 1
else:
ctProducts[productName] = 1
if self.kinetics:
if isinstance(self.kinetics, Arrhenius):
# Create an Elementary Reaction
ctReaction = ct.ElementaryReaction(reactants=ctReactants, products=ctProducts)
elif isinstance(self.kinetics, MultiArrhenius):
# Return a list of elementary reactions which are duplicates
ctReaction = [ct.ElementaryReaction(reactants=ctReactants, products=ctProducts) for arr in self.kinetics.arrhenius]
elif isinstance(self.kinetics, PDepArrhenius):
ctReaction = ct.PlogReaction(reactants=ctReactants, products=ctProducts)
elif isinstance(self.kinetics, MultiPDepArrhenius):
ctReaction = [ct.PlogReaction(reactants=ctReactants, products=ctProducts) for arr in self.kinetics.arrhenius]
elif isinstance(self.kinetics, Chebyshev):
ctReaction = ct.ChebyshevReaction(reactants=ctReactants, products=ctProducts)
elif isinstance(self.kinetics, ThirdBody):
ctReaction = ct.ThreeBodyReaction(reactants=ctReactants, products=ctProducts)
elif isinstance(self.kinetics, Lindemann) or isinstance(self.kinetics, Troe):
ctReaction = ct.FalloffReaction(reactants=ctReactants, products=ctProducts)
else:
raise NotImplementedError('Not able to set cantera kinetics for {0}'.format(self.kinetics))
# Set reversibility, duplicate, and ID attributes
if isinstance(ctReaction,list):
for rxn in ctReaction:
rxn.reversible = self.reversible
# Set the duplicate flag to true since this reaction comes from multiarrhenius or multipdeparrhenius
rxn.duplicate = True
# Set the ID flag to the original rmg index
rxn.ID = str(self.index)
else:
ctReaction.reversible = self.reversible
ctReaction.duplicate = self.duplicate
ctReaction.ID = str(self.index)
self.kinetics.setCanteraKinetics(ctReaction, speciesList)
return ctReaction
else:
raise Exception('Cantera reaction cannot be created because there was no kinetics.')
