postprocess_performance module

This file is part of PyFrac.

Created by Haseeb Zia on 04.03.18. Copyright (c) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE, Switzerland, Geo-Energy Laboratory, 2016-2020. All rights reserved. See the LICENSE.TXT file for more details.

postprocess_performance.get_performance_variable(perf_data, iteration, variable)

This function gets the required variable from the specified iteration.

Parameters

• perf_data (list) – – the loaded performance data in the form of a list of IterationProperties objects.(see properties.IterationProperties for details).

• iteration (string) – – the type of iteration (see properties.IterationProperties for details).

• variable (string) – – the name of the variable to be retrieved.

Returns

• var_list (list) – the loaded variable.

• time_list (list) – the corresponding simulated times at which the variable was collected.

• N_list (list) – the corresponding number of elements in the fracture at the time step at which the variable was collected.

postprocess_performance.load_performance_data(address, sim_name='simulation')

This function loads the performance data in the given simulation. If no simulation name is provided, the most recent simulation will be loaded.

Parameters

• address (string) – – the disk address where the simulation results are saved

• sim_name (string) – – the name of the simulation

Returns

– the loaded performance data in the form of a list of IterationProperties objects.( see properties.IterationProperties for details).

Return type

perf_data (list)

postprocess_performance.plot_performance(address, variable, sim_name='simulation', fig=None, plot_prop=None, plot_vs_N=False)

This function plot the performance variable from the given simulation.

Parameters

• address (string) – – the disk location where the results of the simulation were saved.

• variable (string) –

  – Currently, the following variables are supported:

  variable	meaning
  ’time step attempts’	the number of attempts taken for the time step
  ’fracture front iterations’	fracture front iterations (including the fixed front iteration)
  ’tip inversion iterations’	the iterations taken by the brentq method to converge while inverting the tip asymptote
  ’width constraint iterations’	the iterations taken to converge on closed cells
  ’Picard iterations’	the number of times the linear system is solved
  ’CPU time: time steps’	the CPU time taken by each of the time steps
  ’CPU time: time step attempts’	the CPU time taken by each of the time step attempt

• sim_name (string) – – the name of the simulation.

• fig (Figure) – – a figure to superimpose on

• plot_prop (PlotProperties) – – a PlotProperties object

• plot_vs_N (bool) – – if True, a plot of the variable versus the number of cells will also be plotted.

postprocess_performance.print_performance_data(address, sim_name=None)

This function generate a file with details of all the iterations and the data collected regarding their preformance

Parameters

• address (string) – – the disk location where the results of the simulation were saved.

• sim_name (string) – – the name of the simulation.