pychemia.evaluator package

class pychemia.evaluator.Evaluator[source]

Bases: object

initialize(population)[source]
is_running
run()[source]
stop()[source]
pychemia.evaluator.execute(basedir, command, script)[source]

Utility that copy a given script and execute the given command inside the directory

Parameters:
  • basedir – (str) Basedir of the directory with script
  • command – (str) Command to execute
  • script – (str) Script to call inside basedir

Submodules

pychemia.evaluator.cluster module

pychemia.evaluator.cluster.cluster_evaluator(db_settings, nparal)[source]
pychemia.evaluator.cluster.cluster_launcher(db_settings, nparal)[source]
pychemia.evaluator.cluster.cluster_worker(db_settings)[source]

pychemia.evaluator.cluster_fireball module

pychemia.evaluator.cluster_fireball.cluster_fb_evaluator(db_settings, nparal)[source]
pychemia.evaluator.cluster_fireball.cluster_fb_launcher(db_settings, nparal)[source]
pychemia.evaluator.cluster_fireball.cluster_fb_worker(db_settings)[source]

pychemia.evaluator.direct_evaluator module

class pychemia.evaluator.direct_evaluator.DirectEvaluator(db_settings, dbnames, source_dir, is_evaluated, worker, worker_args=None, nconcurrent=1, evaluate_failed=False, evaluate_all=False, sleeping_time=120)[source]

Bases: object

get_list_candidates()[source]

Scan all databases looking for candidates for evaluation

Returns:A list of pairs, each pair contains the name of the database and candidate identifier.
run()[source]

Continuously search for suitable candidates to evaluation among a list of databases.

Returns:
unlock_all()[source]

Checking all databases and unlocking all entries.

Returns:None

pychemia.evaluator.function module

class pychemia.evaluator.function.FunctionEvaluator[source]

Bases: object

evaluate(i)[source]
initialize(population)[source]
is_running
run()[source]
stop()[source]
class pychemia.evaluator.function.FunctionObjectiveFunction[source]

Bases: object

get_values(selection)[source]
ids_sorted(selection)[source]
initialize(population)[source]

pychemia.evaluator.functional module

class pychemia.evaluator.functional.Evaluator[source]

Bases: object

evaluate(i)[source]
initialize(population)[source]
is_running
run()[source]
stop()[source]
class pychemia.evaluator.functional.ObjectiveFunction[source]

Bases: object

get_values(selection)[source]
ids_sorted(selection)[source]
initialize(population)[source]

pychemia.evaluator.vasp_evaluator module

class pychemia.evaluator.vasp_evaluator.RelaxPopulation(population, basedir, target_force=0.01, target_stress=0.01)[source]

Bases: object

active_workdirs
add_status(entry_id, value)[source]
create_dirs(clean=False)[source]
create_inputs(kp_density=10000, encut=1.0)[source]
del_status(entry_id, value)[source]
flip_status(entry_id, oldvalue, newvalue)[source]
modify_input(entry_id)[source]
run(runner)[source]
set_run(code, runner, basedir, kp_density=10000, encut=1.1)[source]
update(workdir)[source]

This routine determines how to proceed with the relaxation for one specific work directory

Parameters:workdir – (str) String representation of the id in the mongodb
Returns:
update_history(entry_id)[source]
workdirs