AsynchronousEvaluationModel

class pyapprox.models.async_model.AsynchronousEvaluationModel(shell_command, max_eval_concurrency=1, workdir_basename=None, link_filenames=[], params_filename='params.in', results_filename='results.out', params_file_header='', process_sample=None, load_results=None, saved_data_basename=None, save_workdirs='yes', model_name=None)

Bases: object

Evaluate a model in parallel when model instances are invoked by a shell script.

Parameters

process sample: callable function (default=None)

Function that overwrites the basic implementation which reads the sample in from a file called params_filename. This is useful if there are a number of pre-processing steps needed by the model before shall command is executed.

load_results: callable function (default=None)

Function that overwrites the basic implementation which reads the results from a files called results_filename This is useful if there are a number of post-processing steps needed by the model after the shell command is executed. If evaluation fails this function must return None

workdir_basename: string (default=None):

The name of the directory to store local copies or soft links of files. The shell command will be executed in these directories. If None temporary directories with python generated names will be created and then deleted once the shell command has been run.

save_workdirsstring (default=True)

‘no’ - do not save workdirs ‘yes’ - save all files in each workdir ‘limited’ - save only params and results files If workdir_basename is None this variable is ignored the tmp directories that are created will always be deleted.

model_namestring (default=None)

A identifier used when printing model evaluation info

saved_data_basenamestring (default=None)

The basename of the file used to store the output data from the model. A new file is created every time __call__ is exceuted. a unique identifier is created based upon the value of evaluation id when __call__ is started.

Methods Summary

__call__(samples[, opts])	Call self as a function.
asynchronous_evaluate_using_shell_command(…)
cleanup_threads(opts)
create_work_dir()
prepare_values(samples, vals, …)

Methods Documentation

__call__(samples, opts={})

Call self as a function.

asynchronous_evaluate_using_shell_command(sample, opts)

cleanup_threads(opts)

create_work_dir()

prepare_values(samples, vals, completed_function_eval_ids, data_filename)