run() parameters

Main parameters

Parameter Name	Type	Default	Documentation
energy_window	(float,float)	–	Estimated lower and upper bounds of the spectrum. Negative values of the lower bound will be reset to 0 for susceptibilities and conductivity.
max_time	int	-1 = infinite	Maximum runtime in seconds, use -1 to set infinite.
verbosity	int	2 on MPI rank 0, 0 otherwise.	Verbosity level (max level - 3).
t	int	50	Number of elementary updates per global update (\(T\)). Bigger values make the algorithm more ergodic.
f	int	100	Number of global updates (\(F\)); ignored if adjust_f = True. Bigger values make the algorithm more ergodic.
adjust_f	bool	False	Adjust the number of global updates automatically.
l	int	2000	Number of particular solutions used in the final accumulation (\(L\)); ignored if adjust_l = True. Bigger values reduce noise in the final solution / make it smoother.
adjust_l	bool	False	Adjust the number of solutions used in the final accumulation.
make_histograms	bool	False	Accumulate histograms of objective function values.

Fine tuning options

Parameter Name	Type	Default	Documentation
random_seed	int	34788 + 928374 * MPI.rank	Seed for random number generator.
random_name	str	“”	Name of random number generator (MT19937 by default).
max_rects	int	60	Maximum number of rectangles to represent spectra (\(K_{max}\)), should be below 70.
min_rect_width	float	1e-3	Minimal width of a rectangle, in units of the energy window width.
min_rect_weight	float	1e-3	Minimal weight of a rectangle, in units of the requested solution norm.
distrib_d_max	float	2	Maximal parameter of the power-law distribution function for the Metropolis algorithm.
gamma	float	2	Proposal probability parameter \(\gamma\).
adjust_f_range	(int,int)	(100,5000)	Search range for the number of global updates.
adjust_f_l	int	20	Number of particular solutions used to adjust \(F\).
adjust_f_kappa	float	0.25	Limiting value of \(\kappa\) used to adjust \(F\).
adjust_l_range	(int,int)	(100,2000)	Search range for the number of solutions used in the final accumulation.
adjust_l_good_d	float	2.0	Maximal ratio \(D/D_\mathrm{min}\) for a particular solution to be considered good.
adjust_l_verygood_d	float	4/3	Maximal ratio \(D/D_\mathrm{min}\) for a particular solution to be considered very good.
adjust_l_ratio	float	0.95	Critical ratio \(N_\mathrm{very good}/N_\mathrm{good}\) to stop \(L\)-adjustment procedure.
hist_max	float	2.0	Right boundary of the histograms, in units of \(D_\mathrm{min}\) (left boundary is always set to \(D_\mathrm{min}\)).
hist_n_bins	int	100	Number of bins for the histograms.