Quick Plot

class pybamm.QuickPlot(solutions, output_variables=None, labels=None, colors=None, linestyles=None, figsize=None, n_rows=None, time_unit=None, spatial_unit='um', variable_limits='fixed')

Generates a quick plot of a subset of key outputs of the model so that the model outputs can be easily assessed.

Parameters:

• solutions ((iter of) pybamm.Solution or pybamm.Simulation) – The numerical solution(s) for the model(s), or the simulation object(s) containing the solution(s).
• output_variables (list of str, optional) – List of variables to plot
• labels (list of str, optional) – Labels for the different models. Defaults to model names
• colors (list of str, optional) – The colors to loop over when plotting. Defaults to None, in which case the default color loop defined by matplotlib style sheet or rcParams is used.
• linestyles (list of str, optional) – The linestyles to loop over when plotting. Defaults to [“-“, “:”, “–”, “-.”]
• figsize (tuple of floats, optional) – The size of the figure to make
• n_rows (int, optional) – The number of rows to use. If None (default), floor(n // sqrt(n)) is used where n = len(output_variables) so that the plot is as square as possible
• time_unit (str, optional) – Format for the time output (“hours”, “minutes”, or “seconds”)
• spatial_unit (str, optional) – Format for the spatial axes (“m”, “mm”, or “um”)
• variable_limits (str or dict of str, optional) –

  How to set the axis limits (for 0D or 1D variables) or colorbar limits (for 2D variables). Options are:

  • ”fixed” (default): keep all axes fixes so that all data is visible
  • ”tight”: make axes tight to plot at each time
  • dictionary: fine-grain control for each variable, can be either “fixed” or “tight” or a specific tuple (lower, upper).

dynamic_plot(testing=False, step=None)

Generate a dynamic plot with a slider to control the time.

Parameters:

• step (float) – For notebook mode, size of steps to allow in the slider. Defaults to 1/100th of the total time.
• testing (bool) – Whether to actually make the plot (turned off for unit tests)

get_spatial_var(key, variable, dimension)

Return the appropriate spatial variable(s)

plot(t, dynamic=False)

Produces a quick plot with the internal states at time t.

Parameters:t (float) – Dimensional time (in ‘time_units’) at which to plot.

reset_axis()

Reset the axis limits to the default values. These are calculated to fit around the minimum and maximum values of all the variables in each subplot

slider_update(t)

Update the plot in self.plot() with values at new time