site = label.split('_')[2]
if float(cov) < 1. / nsites:
pass
else:
Nsites = int(np.floor(float(cov) * nsites))
occupations[site].append((ads, Nsites))
#populate the lattice
for key, value in occupations.iteritems():
available_sites = sites_list[:]
for ads, Nsites in value:
site = kmos_sites[key]
species = kmos_species[ads]
chosen_sites = random.sample(available_sites, Nsites)
for elem in chosen_sites:
model._put(site=[elem[0], elem[1], 0, site], new_species=species)
available_sites.remove(elem)
model._adjust_database()
#check that lattice occupation is as expected
#model.print_coverages()
#atoms=model.get_atoms()
#view(atoms)
#get DRC for CO adsorption on cus site
process = "CO_adsorption_cus"
#in finite-difference derivative, change rate constant by plus/minus 2%
delta = 0.02
#relax_steps
site = label.split('_')[2]
if float(cov) < 1./nsites:
pass
else:
Nsites = int(np.floor(float(cov)*nsites))
occupations[site].append((ads,Nsites))
#populate the lattice
for key, value in occupations.iteritems():
available_sites = sites_list[:]
for ads,Nsites in value:
site = kmos_sites[key]
species = kmos_species[ads]
chosen_sites = random.sample(available_sites, Nsites)
for elem in chosen_sites:
model._put(site=[elem[0],elem[1],0,site], new_species=species)
available_sites.remove(elem)
model._adjust_database()
#check that lattice occupation is as expected
#model.print_coverages()
#atoms=model.get_atoms()
#view(atoms)
#get DRC for CO adsorption on cus site
process = "CO_adsorption_cus"
#in finite-difference derivative, change rate constant by plus/minus 2%
delta = 0.02
#relax_steps
