westpa.westext.wess package

Submodules

westpa.westext.wess.ProbAdjust module

westpa.westext.wess.ProbAdjust.solve_steady_state(T, U, target_bins_index)

westpa.westext.wess.ProbAdjust.prob_adjust(binprob, rates, uncert, oldindex, targets=[])

westpa.westext.wess.wess_driver module

westpa.westext.wess.wess_driver.check_bool(value, action='warn'): Check that the given value is boolean in type. If not, either raise a warning (if action=='warn') or an exception (action=='raise').

class westpa.westext.wess.wess_driver.RateAverager(bin_mapper, system=None, data_manager=None, work_manager=None)

Bases: object

Calculate bin-to-bin kinetic properties (fluxes, rates, populations) at 1-tau resolution

calculate(iter_start=None, iter_stop=None, n_blocks=1, queue_size=1): Read the HDF5 file and collect flux matrices and population vectors for each bin for each iteration in the range [iter_start, iter_stop). Break the calculation into n_blocks blocks. If the calculation is broken up into more than one block, queue_size specifies the maxmimum number of tasks in the work queue.

extract_data(iter_indices): Extract data from the data_manger and place in dict mirroring the same underlying layout.

task_generator(iter_start, iter_stop, block_size)

westpa.westext.wess.wess_driver.prob_adjust(binprob, rates, uncert, oldindex, targets=[])

westpa.westext.wess.wess_driver.bins_from_yaml_dict(bin_dict)

westpa.westext.wess.wess_driver.reduce_array(Aij): Remove empty rows and columns from an array Aij and return the reduced array Bij and the list of non-empty states

class westpa.westext.wess.wess_driver.WESSDriver(sim_manager, plugin_config)

Bases: object

get_rates(n_iter, mapper): Get rates and associated uncertainties as of n_iter, according to the window size the user has selected (self.windowsize)

prepare_new_iteration()

Module contents

westpa.westext.wess.prob_adjust(binprob, rates, uncert, oldindex, targets=[])

class westpa.westext.wess.WESSDriver(sim_manager, plugin_config)

Bases: object

get_rates(n_iter, mapper): Get rates and associated uncertainties as of n_iter, according to the window size the user has selected (self.windowsize)

prepare_new_iteration()