paddy.utils module

The paddy.utils module contains suporting functions for the paddy.Paddy_Runner module.

Routine listings

get_param_names(p_space)

get_top_fitness(dirty_values)

random_propogation(rand_seed_number, p_space, seed_counter)

paddy_recover(file_name)

paddy.utils.get_param_names(p_space)

Return list of parameter names.

Parameters

p_spaceclass

A class containing attributes exclusively of PaddyParameter instances.

Returns

param_name_listlist of strings

A list of PaddyParameter instances as string types of the instance variable name.

paddy.utils.get_top_fitness(dirty_values)

Return top fitness value.

Returns the top fitness values of a PFARunner, solely, for each iteration as a list when passed a dictionary with the structure type of top_values.

Parameters

dirty_valuesdictionary

A dictionary in the form of top_values.

Returns

fitness_listlist of floats

A list of the top fitness value evaluated for sowing during each itteration.

See also

paddy.Paddy_Runner.PFARunner.run_paddy()

Notes

The top value evaluated for sowing when using ‘population’ for the paddy_type parameter of a PFARunner instance might not be the value of a seed generated during that itteration. See (need to find home for the full description of the PFA)

paddy.utils.paddy_recover(file_name)

Recover pickled paddy file.

Trys to recover the pickled PFARunner instance, and will then use the backup file if there is an issue recovering the origional.

Parameters

file_namestring or nonetype, optional (default

A user defined string that is used as the file handle for PFARunner instance pickling.

Returns

recovered_paddyPFARunner

Depickled PFARunner class instance.

Raises

PaddyRecoveryError

If the recovery of a previous PFARunner fails.

Warning

The pickle module is not secure against malicious data!

See also

paddy.Paddy_Runner.PFARunner.recover_run()

paddy.Paddy_Runner.PFARunner.run_paddy()

pickle.load()

Notes

All functions that the PFARPaddyRecoveryErrorunner instance being recoverd is dependant on need to be defined for successfull depickling, namely the eval_func parameter input.

Examples

>>> import paddy
>>> from paddy.Default_Numerics import *
>>> recovered_PFARunner = paddy.paddy_recover('old_PFARunner')

paddy.utils.random_propogation(rand_seed_number, p_space, seed_counter)

Return updatad seed counter and random seed parameters.

This function takes parameter space and generates random seeds as an array with length determined by the user parameter rand_seed_number and returns the array as well as an updated seed_counter.

See also

paddy.Paddy_Runner.PFARunner.run_paddy()