Code output

Simulation log file

MonteCoffee generates a .txt log file with the naming convention kMClog_#date_#time_.txt. This is handled by the module base.Logging.

The first output contains all the dictionary of parameters, passed as the input parameters when instantiating a NeighborKMC object. This section may look as:

Mikkel Jorgensen (2015-2019)
Noemi Bosio (since 2019)
Elisabeth M. Dietze (since 2020)
Chalmers University of Technology
Goteborg, Sweden
--------------------------------------------------------------------------------
Simulation parameters
pCO       :    2000.0
pO2       :    1000.0
T         :    800.0
Name      :    COOx Simulation
reverses  :    {0: 1, 2: 3, 4: 4, 5: 5}
tend      :    1e-07
Nsites    :    432
--------------------------------------------------------------------------------
No time acceleration used.

Next the log begins with printing the simulation step, the time the log-point was dumped, the simulation time, and the number of events fired, respectively:

Step          time[hr:min:s]             Sim time [s]          Events called
1000             14:47:40             4.84677160781e-10        ['37', '0', '3', '0', '960', '1', '0']
2000             14:47:41             7.10054219544e-10        ['50', '0', '4', '0', '1945', '2', '0']
3000             14:47:42             8.66046768567e-10        ['59', '0', '4', '0', '2936', '2', '0']

The ordering of Events Called is determined by the order of which the parameter events are passed upon instantiating a NeighborKMC object.

Results as .txt files

MonteCoffee generates its output as plain-text (.txt) file for basic output and as object in the HDF5 format for more advanced output, as determined by the method save_txt() in base.NeighborKMC.

If desired, this method can be altered to output other information during runtime. The output files are generated using numpy’s savetxt() method, and can therefore be loaded using np.loadtxt().

The code outputs the following .txt files once prior to simulation:

  • siteids.txt: The index of each site, passed as the parameter ind when instantiating a NeighborKMC.user_sites.Site object. This is useful for storing an Ase.Atoms object.

  • stypes.txt: The site types for each site, passed as the parameter stype when instantiating a NeighborKMC.user_sites.Site object.

During the simulation the following .txt files are updated with a frequency specified in Options:

  • mcstep.txt: The Monte Carlo step corresponding to each line in the other .txt files. This is directly dependent on the updating frequency.

  • time.txt: The simulation time in seconds for every logged Monte Carlo step.

  • coverages.txt: The coverages at each time-step for each lattice-site. The coverages are structured as coverages[mcstep][site_number].

  • evs_exec.txt: The total number of event-type executions. For example, to find the total number of executions of event number 0:

    evs_exec = np.loadtxt("evs_exec.txt")
N1 = evs_exec[0]

  • detail_site_event_evol.hdf5: The detailed time evolution of the system, which saves every step. The file can be read in as follows:

    with h5py.File('detail_site_event_evol.hdf5','a') as f2:
    time_list = np.array(f2["time"])
    event_list = np.array(f2["event"])
    site_list = np.array(f2["site"])
    othersite_list = np.array(f2["othersite"])

Working with this file, one has to be careful, because it can be rather big, despite the compression. In principle hdf5 can be read also with any other hdf5 supporting programming language.

For further information about analyzing output, see Analyze results and Calculating a turnover frequency.