def test_cstr_PE():
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
conditionlist = In_data.load_condition('./WGSdata/')
dEa_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
dBE_index = [4, 5, 6, 7, 8, 9, 10, 11]
a = CSTR(specieslist=specieslist,
reactionlist=reactionlist,
dEa_index=dEa_index,
dBE_index=dBE_index)
a.initialize()
dE_start = np.random.uniform(-20, 20, 20)
dE_start = a.CorrThermoConsis(dE_start)
# print(dE_start)
# print(a.CheckThermoConsis(dE_start))
# for condi in conditionlist:
# print(a.parameter_estimation(dE_start, conditionlist, print_screen=True))
dE, obj = a.parameter_estimation(dE_start,
conditionlist,
print_screen=True)
print(dE, obj)
# parity Plot
expr = []
mkm = []
for kk, condi in enumerate(conditionlist):
mkm.append(a.fwd_simulation(dE, condi)['CO(g)'])
expr.append(condi.TurnOverFrequency['CO(g)'])
# mkm.append(-condi.SimulatedTOF['H2(g)'])
parity_plot(expr, mkm, 'Experimental TOF', 'Microkinetic TOF')
def test_cstr():
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
conditionlist = In_data.load_condition('./WGSdata/')
dEa_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
dBE_index = [4, 5, 6, 7, 8, 9, 10, 11]
a = CSTR(specieslist=specieslist,
reactionlist=reactionlist,
dEa_index=dEa_index,
dBE_index=dBE_index)
a.initialize()
dE_start = np.zeros(20)
for condi in conditionlist:
print(a.fwd_simulation(dE_start, condi))
expr = []
mkm = []
tem = []
for kk, condi in enumerate(conditionlist):
mkm.append(a.fwd_simulation(dE_start, condi)['CO(g)'])
expr.append(condi.TurnOverFrequency['CO(g)'])
# mkm.append(-condi.SimulatedTOF['H2(g)'])
tem.append(condi.Temperature)
parity_plot(expr, mkm, 'Experimental TOF', 'Microkinetic TOF')
import matplotlib.pyplot as plt
plt.figure()
plt.plot(tem, np.log10(mkm), 'k^')
plt.plot(tem, np.log10(expr), 'ro')
def test_new_pe():
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
conditionlist = In_data.load_condition('./WGSdata/')
dEa_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
dBE_index = [4, 5, 6, 7, 8, 9, 10, 11]
a = CSTR(specieslist=specieslist,
reactionlist=reactionlist,
dEa_index=dEa_index,
dBE_index=dBE_index)
a.initialize()
dE_start = np.random.uniform(-20, 20, 20)
dE_start = a.CorrThermoConsis(dE_start)
evidence = {}
evidence['type'] = 'rel'
evidence['err'] = 1
prior = {}
prior['type'] = 'Ridge'
prior['L2'] = 1e-5
prior['lbound'] = [-20] * 20
prior['ubound'] = [20] * 20
dE, obj = a.mle_estimation(dE_start, conditionlist, evidence, prior)
expr = []
mkm = []
for kk, condi in enumerate(conditionlist):
mkm.append(a.fwd_simulation(dE, condi)[0]['CO(g)'])
expr.append(condi.TurnOverFrequency['CO(g)'])
# mkm.append(-condi.SimulatedTOF['H2(g)'])
parity_plot(expr, mkm, 'Experimental TOF', 'Microkinetic TOF')
def test_read_species(species, site):
sitelist = In_data.read_site(site)
specieslist = In_data.read_species(species, sitelist)
assert len(specieslist) == 2
assert specieslist[0].name == 'carbonmonoxide'
assert str(specieslist[0]) == 'CO(g)'
assert specieslist[0].phase == 'gaseous'
assert specieslist[1].name == '*'
assert str(specieslist[1]) == '*'
assert specieslist[1].phase == 'surface'
def test_read_site(site):
sitelist = In_data.read_site(site)
print(str(sitelist[0]))
assert len(sitelist) == 1
assert sitelist[0].name == 'Cu'
assert sitelist[0].metal == 'Cu'
assert sitelist[0].struct == 'FCC'
assert sitelist[0].facet == '111'
def test_cstr_MS_PE():
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
conditionlist = In_data.load_condition('./WGSdata/')
dEa_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
dBE_index = [4, 5, 6, 7, 8, 9, 10, 11]
a = CSTR(specieslist=specieslist,
reactionlist=reactionlist,
dEa_index=dEa_index,
dBE_index=dBE_index)
a.initialize(scale=1e-4)
# dE_start = np.zeros(20)
# a.parameter_estimation(dE_start, conditionlist, print_screen=True, report='%d.txt'%0)
for i in range(200):
dE_start = np.random.uniform(-20, 20, 20)
dE_start = a.CorrThermoConsis(dE_start)
a.parameter_estimation(dE_start,
conditionlist,
print_screen=True,
report='./multi-start/%d.txt' % i)
def test_load():
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
assert str(sitelist[0]) == 'Cu-FCC-111-all'
spenamelist = [
'H2(g)', 'CO(g)', 'CO2(g)', 'H2O(g)', 'H*', 'O*', 'OH*', 'H2O*', 'CO*',
'CO2*', 'HCOO*', 'COOH*', '*'
]
for spe, spename in zip(specieslist, spenamelist):
assert str(spe) == spename
reactionnamelist = [
'CO(g)+*>>CO*', 'H2(g)+2*>>2H*', 'H2O(g)+*>>H2O*', 'CO2(g)+*>>CO2*',
'H2O*+*>>H*+OH*', 'OH*+*>>H*+O*', 'CO*+O*>>CO2*+*', '2OH*>>O*+H2O*',
'CO2*+H*>>HCOO*+*', 'CO*+OH*>>COOH*+*', 'COOH*+*>>CO2*+H*',
'COOH*+OH*>>CO2*+H2O*'
]
for rxn, rxnname in zip(reactionlist, reactionnamelist):
assert str(rxn) == rxnname
import pytest
import tempfile
from AbCD.io_data import In_data
import json
In_data.load_mkm('./testing/WGSdata/')
# test tpd evidence
from AbCD.model import VacuumTPD
from AbCD.io_data import In_data
from AbCD.visual import tpd_profile
sitelist, specieslist, reactionlist = In_data.load_mkm('./testing/TPDdata/')
conditionlist = In_data.load_condition('./testing/TPDdata/')
dEa_index = []
dBE_index = [1]
tpd = VacuumTPD(specieslist=specieslist,
reactionlist=reactionlist,
dEa_index=dEa_index,
dBE_index=dBE_index)
tpd.initialize(pump_level=1)
dP = [-25]
out = tpd.fwd_simulation(dP, conditionlist[0], reltol=1e-12, abstol=1e-12)
_, nd = out.shape
des = [2 * (-out[1, i+1] + out[1, i]) for i in range(nd - 1)]
# tpd_profile(conditionlist[0].TemGrid[:-1], des, r_=[100, 500])
print(conditionlist[0].TemGrid)
prior_info = {}
prior_info['type'] = 'Ridge'
prior_info['L2'] = 1e-5
import pytest
from AbCD.io_data import In_data
from AbCD import CSTR
import numpy as np
sitelist, specieslist, reactionlist = In_data.load_mkm('./WGSdata/')
conditionlist = In_data.load_condition('./WGSdata/')
dBE_index = [4, 5, 6, 7, 8, 9, 10, 11]
dEa_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
def test_cstr_build():
wgs_cstr = CSTR(specieslist=specieslist,
reactionlist=reactionlist,
dBE_index=dBE_index,
dEa_index=dEa_index)
assert wgs_cstr.Pnlp.shape[0] == len(dEa_index) + len(dBE_index)
wgs_cstr.initialize()
E = 0 * np.ones(len(dEa_index) + len(dBE_index))
E = wgs_cstr.CorrThermoConsis(E)
assert wgs_cstr.CheckThermoConsis(E)
for condi in conditionlist:
tor, _ = wgs_cstr.fwd_simulation(E, condi, reltol=1e-12, abstol=1e-14)
print(tor)
if __name__ == "__main__":
test_cstr_build()