tick.plot.plot_history¶

tick.plot.plot_history(solvers, x='n_iter', y='obj', labels=None, show=True, log_scale: bool = False, dist_min: bool = False, rendering: str = 'matplotlib', ax=None)[source]¶

Plot the history of convergence of learners or solvers.

It is used to compare easily their convergence performance.

Parameters

solvers : list of object with and history to plot, namely solvers

(children of tick.solver.base.Solver) or learners (children of tick.hawkes.inference.base.LearnerOptim)

x : str, default=’n_iter’

if ‘n_iter’ : iteration number

if ‘time’ : computation time

y : str, default=’obj’

if ‘obj’the objective (value of the function minimized).
Other choices are possible, any of those present in the history

labels : list of str, default=None

Label of each solver in the legend. If set to None then the class name of each solver will be used.

show : bool, default=`True`

if True, show the plot. Otherwise an explicit call to the show function is necessary. Useful when superposing several plots.

log_scale : bool, default=`False`

If True, then y-axis is on a log-scale

dist_min : bool, default=`False`

If True, plot the difference between y of each solver and the minimal y of all solvers. This is useful when comparing solvers on a logarithmic scale, to illustrate linear convergence of algorithms

rendering : {‘matplotlib’, ‘bokeh’}, default=’matplotlib’