ZacrosSteadyStateResults

The ZacrosSteadyStateResults class was designed to take charge of the job folder after executing the ZacrosSteadyStateJob. It gathers the information from the output files and helps to extract data of interest from them. Every ZacrosSteadyStateJob instance has an associated ZacrosSteadyStateResults instance created automatically on job creation and stored in its results attribute. This class extends the PLAMS Results class.

The following lines of code show an example of how to use the ZacrosSteadyStateResults class:

 1ss_sett = pz.Settings()
 2ss_sett.turnover_frequency.nbatch = 20
 3ss_sett.turnover_frequency.confidence = 0.96
 4ss_sett.nreplicas = 2
 5
 6params = pz.ZacrosSteadyStateJob.Parameters()
 7params.add( 'max_time', 'restart.max_time', numpy.arange(20.0, 100.0, 20.0) )
 8print(params)
 9
10ss_job = pz.ZacrosSteadyStateJob( settings=ss_sett, reference=job, parameters=params )
11results = ss_job.run()
12
13if ss_job.ok():
14   print(results.history()[0])
15
16   print("%8s"%"iter", "%10s"%"TOF_CO2", "%15s"%"max_time",
17         "%15s"%"TOF_CO2_error", "%10s"%"conv?")
18
19   for i,step in enumerate(results.history()):
20      print("%8d"%i,
21            "%10.5f"%step['turnover_frequency']['CO2'],
22            "%15d"%step['max_time'],
23            "%15.5f"%step['turnover_frequency_error']['CO2'],
24            "%10s"%(all(step['converged'].values())))

Lines 1-11 were already discussed before (see ZacrosSteadyStateJob). Here, the ZacrosSteadyStateResults object results is created by calling the method run() of the corresponding ZacrosSteadyStateJob job (line 11).

Afterward, the method ok() is invoked to assure that the calculation finished appropriately (line 13), and only after that, it is good to go to get information from the output files by using the ZacrosSteadyStateResults methods (lines 14-24). In this example, we want to print information about the history of the calculation after each iteration. Line 14 prints the first item of the list returned by the history() method to show its structure. Then after line 16, we show this information for all iterations summarized in a table.

The execution of the code above after line 13 shows the following information to the standard output:

{'turnover_frequency': {'CO': -0.75409, 'O2': -0.39222, 'CO2': 0.75498},
 'turnover_frequency_error': {'CO': 0.11055, 'O2': 0.06458, 'CO2': 0.11099},
 'converged': {'CO': False, 'O2': False, 'CO2': False},
 'max_time': 20.0}

 iter    TOF_CO2        max_time   TOF_CO2_error      conv?
    0    0.75498              20         0.11099      False
    1    0.63210              40         0.03387      False
    2    0.62030              60         0.02156       True

As you can see in the output, each element of the history includes the maximum amount of time (referred to as max time) used in that iteration as well as three numbers related to the turnover frequency calculation: the value itself (referred to as turnover frequency), its error (referred to as turnover frequency error), and a flag (referred to as turnover frequency converged) that denotes whether or not the calculation has converged. Finally, lines 14-18 show the values of x_CO and TOF_CO2 for all compositions in a summary table.

API

class ZacrosSteadyStateResults(job)

A Class for handling ZacrosSteadyStateJob Results.

history(pos=None)

Returns a list of properties related with the history of the calculation. Each element of the history includes the maximum amount of time (referred to as max_steps, max_time, or wall_time) used in that iteration as well as three numbers related to the turnover frequency calculation: the value itself (referred to as turnover frequency), its error (referred to as turnover frequency error), and a flag (referred to as turnover frequency converged) that denotes whether or not the calculation has converged.

Example of an item of the returned history list:

{'turnover_frequency': {'CO': -0.75409, 'O2': -0.39222, 'CO2': 0.75498},
 'turnover_frequency_error': {'CO': 0.11055, 'O2': 0.06458, 'CO2': 0.11099},
 'converged': {'CO': False, 'O2': False, 'CO2': False},
 'max_time': 20.0}
niterations()

Returns the current number of iterations executed

nreplicas()

Returns the number of replicas used

children_results(iteration=None, replica=None)

Returns a list of the children’s results or the results for a specific iteration or replica if requested.

get_zacros_version()

Returns the zacros’s version from the ‘general_output.txt’ file.

get_reaction_network()

Returns the reactions from the ‘general_output.txt’ file associated to the last children.

provided_quantities()

Returns the provided quantities headers from the specnum_output.txt file in a list associated to the last children.

number_of_lattice_sites()

Returns the number of lattice sites from the ‘general_output.txt’ file associated to the last children.

gas_species_names()

Returns the gas species names from the ‘general_output.txt’ file associated to the last children.

surface_species_names()

Returns the surface species names from the ‘general_output.txt’ file associated to the last children.

site_type_names()

Returns the site types from the ‘general_output.txt’ file associated to the last children.

number_of_snapshots()

Returns the number of configurations from the ‘history_output.txt’ file associated to the last children.

number_of_process_statistics()

Returns the number of process statistics from the ‘procstat_output.txt’ file associated to the last children.

elementary_steps_names()

Returns the names of elementary steps from the ‘procstat_output.txt’ file associated to the last children.

lattice_states(last=None)

Returns the configurations from the ‘history_output.txt’ file associated to the last children.

last_lattice_state()

Returns the last configuration from the ‘history_output.txt’ file associated to the last children.

average_coverage(last=5)

Returns a dictionary with the average coverage fractions using the last last lattice states, e.g., { "CO*":0.32, "O*":0.45 }. It makes an average on the number of replicas if they were requested.

plot_lattice_states(data, pause=-1, show=True, ax=None, close=False, time_perframe=0.5, file_name=None)

Uses Matplotlib to create an animation of the lattice states associated to the last children.

  • data – List of LatticeState objects to plot

  • pause – After showing the figure, it will wait pause-seconds before refreshing.

  • show – Enables showing the figure on the screen.

  • ax – The axes of the plot. It contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. See matplotlib.axes.

  • close – Closes the figure window after pause time.

  • time_perframe – Sets the time interval between frames in seconds.

  • file_name – Saves the figures to the file file_name-<id> (the corresponding id on the list replaces the <id>). The format is inferred from the extension, and by default, .png is used.

plot_molecule_numbers(species_name, pause=-1, show=True, ax=None, close=False, file_name=None, normalize_per_site=False, derivative=False)

uses Matplotlib to create an animation of the Molecule Numbers associated to the last children.

  • species_name – List of species names to show, e.g., ["CO*", "CO2"]

  • pause – After showing the figure, it will wait pause-seconds before refreshing. This can be used for crude animation.

  • show – Enables showing the figure on the screen.

  • ax – The axes of the plot. It contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. See matplotlib.axes.

  • close – Closes the figure window after pause time.

  • file_name – Saves the figure to the file file_name. The format is inferred from the extension, and by default, .png is used.

  • normalize_per_site – Divides the molecule numbers by the total number of sites in the lattice.

  • derivative – Plots the first derivative.

get_process_statistics()

Returns the statistics from the ‘procstat_output.txt’ file in a form of a list of dictionaries associated to the last children.

plot_process_statistics(data, key, log_scale=False, pause=-1, show=True, ax=None, close=False, file_name=None)

Uses Matplotlib to create an animation of the process statistics associated to the last children.

  • data – List of process statistics to plot. See function get_process_statistics().

  • key – Key to plot, e.g., 'average_waiting_time', 'average_waiting_time'. See function get_process_statistics().

  • log_scale – Use log scale for the x axis.

  • pause – After showing the figure, it will wait pause-seconds before refreshing.

  • show – Enables showing the figure on the screen.

  • ax – The axes of the plot. It contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. See matplotlib.axes.

  • close – Closes the figure window after pause time.

  • file_name – Saves the figures to the file file_name-<id> (the corresponding id on the list replaces the <id>). The format is inferred from the extension, and by default, .png is used.