ogstools.logparser.plots module#

ogstools.logparser.plots.plot_convergence_order(df, n=3, x_metric='time_step', **kwargs)[source]#

Create a heatmap of the nonlinear solver convergence order.

see: convergence_order_per_ts_iteration() In order to estimate the convergence order we need to take into account multiple values and thus cannot assign each iteration a convergence order. Only for iterations i of i >= n an order is calculated and plotted. Per default the scale is limited to a range of 0 to 2 to limit the view to meaningful data. Set the keyword arguments vmin and vmax`to `None to see the entire scale.

Parameters:

  • df (DataFrame) – Dataframe of a simulation log.

  • n (Literal[3, 4]) – Number of error values to use to estimate the convergence order.

  • x_metric (Literal['time_step', 'model_time']) – x_axis can represent either “time_step” or “model_time”

Return type:

Figure

Keyword Arguments:
Return type:

Figure

Returns:

A figure with a heatmap of the nonlinear solver convergence order.

ogstools.logparser.plots.plot_convergence(df, metric='dx', x_metric='time_step', **kwargs)[source]#

Create a heatmap of the nonlinear solver convergence data.

The individual values in the heatmap correspond to the top right indices on the x- and y-axis. E.g. the very first entry which fills the space between timesteps 0-1 and iteration 0-1 belongs to the first iteration of the first timestep. Thus we immediately read on which iteration a timestep converged and on which timestep the simulation ended. Per default logarithmic scaling is used. Set log_scaled to False to use linear scaling.

Parameters:

  • df (DataFrame) – Dataframe of a simulation log.

  • metric (Literal['dx', 'dx_x', 'x']) – Which metric / column of the Dataframe to plot. dx (absolute error), dx_x (relative error), x (residual)

  • x_metric (Literal['time_step', 'model_time']) – x_axis can represent either “time_step” or “model_time”

Return type:

Figure

Keyword Arguments:
Return type:

Figure

Returns:

A figure with a heatmap of the nonlinear solver convergence data.