def run(i=0, edir=''): from sys import path path.append(edir) from kmos.run import KMC_Model model = KMC_Model(banner=False, print_rates=False) model.settings.random_seed = i assert not model.do_steps(1000) assert not model.deallocate()
def run(i=0, edir=''): from sys import path path.append(edir) from kmos.run import KMC_Model model = KMC_Model(banner=False, print_rates=False) model.settings.random_seed = i assert not model.do_steps(1000) assert not model.deallocate()
def main(args=None): """The CLI main entry point function. The optional argument args, can be used to directly supply command line argument like $ kmos <args> otherwise args will be taken from STDIN. """ from glob import glob options, args, parser = get_options(args, get_parser=True) global model, pt, np, cm_model if not args[0] in usage.keys(): args[0] = match_keys(args[0], usage, parser) if args[0] == 'benchmark': from sys import path path.append(os.path.abspath(os.curdir)) nsteps = 1000000 from time import time from kmos.run import KMC_Model model = KMC_Model(print_rates=False, banner=False) time0 = time() try: model.proclist.do_kmc_steps(nsteps) except: # kmos < 0.3 had no model.proclist.do_kmc_steps model.do_steps(nsteps) needed_time = time() - time0 print('Using the [%s] backend.' % model.get_backend()) print('%s steps took %.2f seconds' % (nsteps, needed_time)) print('Or %.2e steps/s' % (1e6 / needed_time)) model.deallocate() elif args[0] == 'build': from kmos.utils import build build(options) elif args[0] == 'edit': from kmos import gui gui.main() elif args[0] == 'settings-export': import kmos.types import kmos.io from kmos.io import ProcListWriter if len(args) < 2: parser.error('XML file and export path expected.') if len(args) < 3: out_dir = '%s_%s' % (os.path.splitext(args[1])[0], options.backend) print('No export path provided. Exporting to %s' % out_dir) args.append(out_dir) xml_file = args[1] export_dir = args[2] project = kmos.types.Project() project.import_file(xml_file) writer = ProcListWriter(project, export_dir) writer.write_settings() elif args[0] == 'export': import kmos.types import kmos.io from kmos.utils import build if len(args) < 2: parser.error('XML file and export path expected.') if len(args) < 3: out_dir = '%s_%s' % (os.path.splitext(args[1])[0], options.backend) print('No export path provided. Exporting to %s' % out_dir) args.append(out_dir) xml_file = args[1] export_dir = os.path.join(args[2], 'src') project = kmos.types.Project() project.import_file(xml_file) project.shorten_names(max_length=options.variable_length) kmos.io.export_source(project, export_dir, options=options) if ((os.name == 'posix' and os.uname()[0] in ['Linux', 'Darwin']) or os.name == 'nt') \ and not options.source_only: os.chdir(export_dir) build(options) for out in glob('kmc_*'): if os.path.exists('../%s' % out): if options.overwrite: overwrite = 'y' else: overwrite = raw_input( ('Should I overwrite existing %s ?' '[y/N] ') % out).lower() if overwrite.startswith('y'): print('Overwriting {out}'.format(**locals())) os.remove('../%s' % out) shutil.move(out, '..') else: print('Skipping {out}'.format(**locals())) else: shutil.move(out, '..') elif args[0] == 'settings-export': import kmos.io pt = kmos.io.import_file(args[1]) if len(args) < 3: out_dir = os.path.splitext(args[1])[0] print('No export path provided. Exporting kmc_settings.py to %s' % out_dir) args.append(out_dir) if not os.path.exists(args[2]): os.mkdir(args[2]) elif not os.path.isdir(args[2]): raise UserWarning("Cannot overwrite %s; Exiting;" % args[2]) writer = kmos.io.ProcListWriter(pt, args[2]) writer.write_settings() elif args[0] == 'help': if len(args) < 2: parser.error('Which help do you want?') if args[1] == 'all': for command in sorted(usage): print(usage[command]) elif args[1] in usage: print('Usage: %s\n' % usage[args[1]]) else: arg = match_keys(args[1], usage, parser) print('Usage: %s\n' % usage[arg]) elif args[0] == 'import': import kmos.io if not len(args) >= 2: raise UserWarning('XML file name expected.') pt = kmos.io.import_xml_file(args[1]) if len(args) == 2: sh(banner='Note: pt = kmos.io.import_xml(\'%s\')' % args[1]) elif len( args ) == 3: # if optional 3rd argument is given, store model there and exit pt.save(args[2]) elif args[0] == 'rebuild': from time import sleep print('Will rebuild model from kmc_settings.py in current directory') print('Please do not interrupt,' ' build process, as you will most likely') print('loose the current model files.') sleep(2.) from sys import path path.append(os.path.abspath(os.curdir)) from tempfile import mktemp if not os.path.exists('kmc_model.so') \ and not os.path.exists('kmc_model.pyd'): raise Exception('No kmc_model.so found.') if not os.path.exists('kmc_settings.py'): raise Exception('No kmc_settings.py found.') from kmos.run import KMC_Model model = KMC_Model(print_rates=False, banner=False) tempfile = mktemp() f = file(tempfile, 'w') f.write(model.xml()) f.close() for kmc_model in glob('kmc_model.*'): os.remove(kmc_model) os.remove('kmc_settings.py') main('export %s -b %s .' % (tempfile, options.backend)) os.remove(tempfile) model.deallocate() elif args[0] in ['run', 'shell']: from sys import path path.append(os.path.abspath(os.curdir)) from kmos.run import KMC_Model # useful to have in interactive mode import numpy as np try: from matplotlib import pyplot as plt except: plt = None if options.catmap: import catmap import catmap.cli.kmc_runner seed = catmap.cli.kmc_runner.get_seed_from_path('.') cm_model = catmap.ReactionModel(setup_file='{seed}.mkm'.format( **locals())) catmap_message = '\nSide-loaded catmap_model {seed}.mkm into cm_model = ReactionModel(setup_file="{seed}.mkm")'.format( **locals()) else: catmap_message = '' try: model = KMC_Model(print_rates=False) except: print("Warning: could not import kmc_model!" " Please make sure you are in the right directory") sh(banner='Note: model = KMC_Model(print_rates=False){catmap_message}'. format(**locals())) try: model.deallocate() except: print("Warning: could not deallocate model. Was is allocated?") elif args[0] == 'version': from kmos import VERSION print(VERSION) elif args[0] == 'view': from sys import path path.append(os.path.abspath(os.curdir)) from kmos import view view.main(steps_per_frame=options.steps_per_frame) elif args[0] == 'xml': from sys import path path.append(os.path.abspath(os.curdir)) from kmos.run import KMC_Model model = KMC_Model(banner=False, print_rates=False) print(model.xml()) else: parser.error('Command "%s" not understood.' % args[0])
import math from kmos.run import KMC_Model model = KMC_Model(banner=False) model.parameters.p_COgas = 2.e-1 model.parameters.p_O2gas = 1.e-1 nrel = 1e7 nsample = 1e7 # numerical parameters Ts = range(450, 650, 20) # 20 values between 450 and 650 K TOFs = [] # empty list for output # Loop over the temperature for T in Ts: model.parameters.T = T # Set the temperature model.do_steps(nrel) # Relax the system # Sample the reactivity output = model.get_std_sampled_data(1, nsample, output='dict') # Collect output TOFs.append(output['CO_oxidation']) # Transform the variables invTs = [1 / float(T) for T in Ts] logTOFs = [math.log(TOF, 10.) for TOF in TOFs] # and plot import matplotlib.pyplot as plt plt.plot(invTs, logTOFs, '-o') plt.xlabel('1/T [1/K]') plt.ylabel('log(TOF) / events (sites s)^-1') plt.savefig('arrhenius.pdf') # Optionally, save plot
def main(args=None): """The CLI main entry point function. The optional argument args, can be used to directly supply command line argument like $ kmos <args> otherwise args will be taken from STDIN. """ from glob import glob options, args, parser = get_options(args, get_parser=True) if not args[0] in usage.keys(): args[0] = match_keys(args[0], usage, parser) if args[0] == 'benchmark': from sys import path path.append(os.path.abspath(os.curdir)) nsteps = 1000000 from time import time from kmos.run import KMC_Model model = KMC_Model(print_rates=False, banner=False) time0 = time() try: model.proclist.do_kmc_steps(nsteps) except: # kmos < 0.3 had no model.proclist.do_kmc_steps model.do_steps(nsteps) needed_time = time() - time0 print('Using the [%s] backend.' % model.get_backend()) print('%s steps took %.2f seconds' % (nsteps, needed_time)) print('Or %.2e steps/s' % (1e6 / needed_time)) model.deallocate() elif args[0] == 'build': from kmos.utils import build build(options) elif args[0] == 'edit': from kmos import gui gui.main() elif args[0] == 'settings-export': import kmos.types import kmos.io from kmos.io import ProcListWriter if len(args) < 2: parser.error('XML file and export path expected.') if len(args) < 3: out_dir = os.path.splitext(args[1])[0] print('No export path provided. Exporting to %s' % out_dir) args.append(out_dir) xml_file = args[1] export_dir = args[2] project = kmos.types.Project() project.import_xml_file(xml_file) writer = ProcListWriter(project, export_dir) writer.write_settings() elif args[0] == 'export': import kmos.types import kmos.io from kmos.utils import build if len(args) < 2: parser.error('XML file and export path expected.') if len(args) < 3: out_dir = '%s_%s' % (os.path.splitext(args[1])[0], options.backend) print('No export path provided. Exporting to %s' % out_dir) args.append(out_dir) xml_file = args[1] export_dir = os.path.join(args[2], 'src') project = kmos.types.Project() project.import_xml_file(xml_file) kmos.io.export_source(project, export_dir, code_generator=options.backend) if ((os.name == 'posix' and os.uname()[0] == 'Linux') or os.name == 'nt') \ and not options.source_only: os.chdir(export_dir) build(options) for out in glob('kmc_*'): if os.path.exists('../%s' % out): overwrite = raw_input(('Should I overwrite existing %s ?' '[y/N] ') % out).lower() if overwrite.startswith('y'): os.remove('../%s' % out) shutil.move(out, '..') else: shutil.move(out, '..') elif args[0] == 'settings-export': import kmos.io pt = kmos.io.import_xml_file(args[1]) if len(args) < 3: out_dir = os.path.splitext(args[1])[0] print('No export path provided. Exporting kmc_settings.py to %s' % out_dir) args.append(out_dir) if not os.path.exists(args[2]): os.mkdir(args[2]) elif not os.path.isdir(args[2]): raise UserWarning("Cannot overwrite %s; Exiting;" % args[2]) writer = kmos.io.ProcListWriter(pt, args[2]) writer.write_settings() elif args[0] == 'help': if len(args) < 2: parser.error('Which help do you want?') if args[1] == 'all': for command in sorted(usage): print(usage[command]) elif args[1] in usage: print('Usage: %s\n' % usage[args[1]]) else: arg = match_keys(args[1], usage, parser) print('Usage: %s\n' % usage[arg]) elif args[0] == 'import': import kmos.io if not len(args) >= 2: raise UserWarning('XML file name expected.') global pt pt = kmos.io.import_xml_file(args[1]) sh(banner='Note: pt = kmos.io.import_xml(\'%s\')' % args[1]) elif args[0] == 'rebuild': from time import sleep print('Will rebuild model from kmc_settings.py in current directory') print('Please do not interrupt,' ' build process, as you will most likely') print('loose the current model files.') sleep(2.) from sys import path path.append(os.path.abspath(os.curdir)) from tempfile import mktemp if not os.path.exists('kmc_model.so') \ and not os.path.exists('kmc_model.pyd'): raise Exception('No kmc_model.so found.') if not os.path.exists('kmc_settings.py'): raise Exception('No kmc_settings.py found.') from kmos.run import KMC_Model model = KMC_Model(print_rates=False, banner=False) tempfile = mktemp() f = file(tempfile, 'w') f.write(model.xml()) f.close() for kmc_model in glob('kmc_model.*'): os.remove(kmc_model) os.remove('kmc_settings.py') main('export %s -b %s .' % (tempfile, options.backend)) os.remove(tempfile) model.deallocate() elif args[0] in ['run', 'shell']: from sys import path path.append(os.path.abspath(os.curdir)) from kmos.run import KMC_Model # useful to have in interactive mode import numpy as np try: from matplotlib import pyplot as plt except: plt = None try: model = KMC_Model(print_rates=False) except: print("Warning: could not import kmc_model!" " Please make sure you are in the right directory") global model, np sh(banner='Note: model = KMC_Model(print_rates=False)') try: model.deallocate() except: print("Warning: could not deallocate model. Was is allocated?") elif args[0] == 'version': from kmos import VERSION print(VERSION) elif args[0] == 'view': from sys import path path.append(os.path.abspath(os.curdir)) from kmos import view view.main(steps_per_frame=options.steps_per_frame) elif args[0] == 'xml': from sys import path path.append(os.path.abspath(os.curdir)) from kmos.run import KMC_Model model = KMC_Model(banner=False, print_rates=False) print(model.xml()) else: parser.error('Command "%s" not understood.' % args[0])
#prepare arrays for TOFs, coverages and kmc steps tofs = np.zeros((N, len(tof_labels))) covs = np.zeros((N, len(cov_labels))) steps = np.zeros((N, 1)) #run model and save data for i in range(N): atoms = model.get_atoms(geometry=False) tof = atoms.tof_integ tofs[i, :] = tof cov = atoms.occupation covs[i, :] = cov.flatten() step = atoms.kmc_step steps[i] = step model.do_steps(sample_step) #prepare figure and plot colors fig = pylab.figure() colors = [ "#0065bd", "#a2ad00", "#e37222", "#B452CD", "#dad7cb", "#000000", "r" ] #plot TOFs ax = fig.add_subplot(2, 1, 1) for i in range(len(tof_labels)): ax.plot(steps, tofs[:, i], color=colors[i], label='CO2') ax.set_xlabel('kmc steps') ax.set_ylabel(ur'TOF (s$^{-1}$site$^{-1}$)') #pylab.ylim([0,5]) box = ax.get_position()
n_relax = 1e7 n_sample = 1e7 eps_f = 0.02 e_int = 0.002 thetas = np.linspace(0.1, 0.9, 9) # current vs. concentration currents = [] for theta in thetas: model = KMC_Model(banner=False) model.parameters.thetaS = theta model.parameters.thetaD = theta model.parameters.eps_f = eps_f model.parameters.e_int = e_int model.do_steps(n_relax) exit0 = (model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry)) t0 = model.base.get_kmc_time() model.do_steps(n_sample) currents.append( (model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry) - exit0) / (model.base.get_kmc_time() - t0) / float(model.size[1])) model.deallocate() fig, ax = plt.subplots(1) ax.plot(thetas, currents, '-o') ax.set_xlabel('Concentration')
""" import math from kmos.run import KMC_Model model = KMC_Model(banner = False) model.parameters.p_COgas = 2.e-1 model.parameters.p_O2gas = 1.e-1 nrel = 1e7; nsample = 1e7 # numerical parameters Ts = range(450,650,20) # 20 values between 450 and 650 K TOFs = [] # empty list for output # Loop over the temperature for T in Ts: model.parameters.T = T # Set the temperature model.do_steps(nrel) # Relax the system # Sample the reactivity output = model.get_std_sampled_data(1, nsample, output='dict') # Collect output TOFs.append(output['CO_oxidation']) # Transform the variables invTs = [1/float(T) for T in Ts] logTOFs = [math.log(TOF,10.) for TOF in TOFs] # and plot import matplotlib.pyplot as plt plt.plot(invTs, logTOFs, '-o') plt.xlabel('1/T [1/K]') plt.ylabel('log(TOF) / events (sites s)^-1') plt.savefig('arrhenius.pdf') # Optionally, save plot
from kmos.run import KMC_Model import random Ts = [350, 450] kads = 3e-3 size = (30, 30, 30) targetML = 4. nsteps = 100 for i, T in enumerate(Ts): random_seed = random.random() * 1e12 model = KMC_Model(banner=False, size=size, random_seed=random_seed) model.parameters.T = T model.parameters.kads = kads tsim = 0.0 ML = 0.0 while ML < targetML: model.do_steps(nsteps) at = model.get_atoms(geometry=False) # Convert TOF into ML growth ML += at.tof_data[model.tofs.index('Growth')] * at.delta_t * size[2] outname = '_'.join(['config', 'T{}'.format(T)] + ['{}'.format(d) for d in model.size]) model.dump_config(outname) print('Finished with T={}K'.format(T)) print('Deposited {}ML in {} s'.format(ML, model.base.get_kmc_time())) model.deallocate()
#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 relax_steps = 1e6 #sample_steps sample_steps = 1e7 #relax model model.do_steps(relax_steps) atoms = model.get_atoms(geometry=False) #get rate constant k = float(model.rate_constants(process).split('=')[1][1:-8]) #get initial TOF k_ini = k * (1 - delta) model.rate_constants.set("CO_adsorption_cus", k_ini) data = model.get_std_sampled_data(samples=1, sample_size=sample_steps, tof_method="integ") tof_ini = float(data.split(' ')[3]) #get final TOF k_fin = k * (1 + delta)
n_relax = 1e7 n_sample = 1e7 eps_f = 0.02 e_int = 0.002 thetas = np.linspace(0.1, 0.9, 9) # current vs. concentration currents = [] for theta in thetas: model = KMC_Model(banner=False) model.parameters.thetaS = theta model.parameters.thetaD = theta model.parameters.eps_f = eps_f model.parameters.e_int = e_int model.do_steps(n_relax) exit0 = (model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry)) t0 = model.base.get_kmc_time() model.do_steps(n_sample) currents.append((model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry) - exit0) / (model.base.get_kmc_time() - t0) / float(model.size[1])) model.deallocate() fig, ax = plt.subplots(1) ax.plot(thetas, currents, '-o') ax.set_xlabel('Concentration') ax.set_ylabel('Current')
Ts = [350, 450] kads = 3e-3 size = (30, 30, 30) targetML = 4. nsteps = 100 for i,T in enumerate(Ts): random_seed = random.random()*1e12 model = KMC_Model(banner=False, size = size, random_seed = random_seed) model.parameters.T = T model.parameters.kads = kads tsim = 0.0 ML = 0.0 while ML < targetML: model.do_steps(nsteps) at = model.get_atoms(geometry=False) # Convert TOF into ML growth ML += at.tof_data[model.tofs.index('Growth')]*at.delta_t*size[2] outname = '_'.join(['config', 'T{}'.format(T)] + ['{}'.format(d) for d in model.size]) model.dump_config(outname) print('Finished with T={}K'.format(T)) print('Deposited {}ML in {} s'.format( ML, model.base.get_kmc_time())) model.deallocate()
#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 relax_steps = 1e6 #sample_steps sample_steps = 1e7 #relax model model.do_steps(relax_steps) atoms = model.get_atoms(geometry=False) #get rate constant k = float(model.rate_constants(process).split('=')[1][1:-8]) #get initial TOF k_ini = k*(1-delta) model.rate_constants.set("CO_adsorption_cus", k_ini) data = model.get_std_sampled_data(samples=1,sample_size=sample_steps,tof_method="integ") tof_ini = float(data.split(' ')[3]) #get final TOF k_fin = k*(1+delta) model.rate_constants.set("CO_adsorption_cus", k_fin) data = model.get_std_sampled_data(samples=1,sample_size=sample_steps,tof_method="integ")
#prepare arrays for TOFs, coverages and kmc steps tofs = np.zeros((N,len(tof_labels))) covs = np.zeros((N,len(cov_labels))) steps = np.zeros((N,1)) #run model and save data for i in range(N): atoms = model.get_atoms(geometry=False) tof = atoms.tof_integ tofs[i,:] = tof cov = atoms.occupation covs[i,:] = cov.flatten() step = atoms.kmc_step steps[i] = step model.do_steps(sample_step) #prepare figure and plot colors fig = pylab.figure() colors = ["#0065bd","#a2ad00","#e37222","#B452CD","#dad7cb","#000000","r"] #plot TOFs ax = fig.add_subplot(2,1,1) for i in range(len(tof_labels)): ax.plot(steps, tofs[:,i], color=colors[i], label='CO2') ax.set_xlabel('kmc steps') ax.set_ylabel(ur'TOF (s$^{-1}$site$^{-1}$)') #pylab.ylim([0,5]) box = ax.get_position() ax.set_position([box.x0, box.y0, box.width * 0.8, box.height]) ax.legend(bbox_to_anchor=(1, 0.916), bbox_transform=pylab.gcf().transFigure)
NREL = 1e7 NSAMPLE = 5e7 # current vs field theta = 0.5 currents = [] fields = np.linspace(0.005, 0.04, 10) for eps_f in fields: model = KMC_Model(banner = False, size = [L, H]) model.parameters.thetaS = theta model.parameters.thetaD = theta model.parameters.eps_f = eps_f model.do_steps(NREL) exit0 = (model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry)) t0 = model.base.get_kmc_time() model.do_steps(NSAMPLE) currents.append( ( model.base.get_procstat(model.proclist.drain_exit) - model.base.get_procstat(model.proclist.drain_entry) - exit0) / (model.base.get_kmc_time() - t0) / float(L)) model.deallocate() fig = plt.figure(figsize = (8, 5)) plt.plot(fields, currents, '-o') plt.xlabel('Field contribution [eV]') plt.ylabel('Current [ ions / (s site) ]') plt.savefig('current_vs_field.pdf')