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:
- see: - heatmap())
 
 - Returns:
- A figure with a heatmap of the nonlinear solver convergence order. 
- Return type:
- Figure 
 
- 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_scale 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:
- see: - heatmap())
 
 - Returns:
- A figure with a heatmap of the nonlinear solver convergence data. 
- Return type:
- Figure 
 
 
    