.. _hero-py:


#######
hero.py
#######

**********************
class Hero(Optimizer):
**********************

SIMO metaheuristic HERO optimization algorithm.

Initialize with arameters::

    repeats=10
    initial_solutions=100
    maximum_iterations=100


def __init__(self, logger, logname, optlogger, taskdef, simdbin, opdbin, simdbout, opdbout, \*\*keywords):
==========================================================================================================

Initialize optimizer::

    >>> epsilon = 0.00001
    >>> from simo.optimization.hero import HERO
    >>> execfile('optimization/test/mocks4optimizer.py')
    >>> chart_path = 'optimization/test'

    >>> hero = HERO(logger, logname, taskdef, simdbin, simdbout, False, False,
    ...             False, chart_path, True, 'test', True,
    ...             keyword1='test-kw')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "repeats" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "initial_solutions" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "maximum_iterations" missing!')

    >>> hero = HERO(logger, logname, taskdef, simdbin, simdbout, False, False,
    ...             False, chart_path, True, 'test', True,
    ...             repeats=2,
    ...             initial_solutions=3,
    ...             maximum_iterations=2)


def optimize(self):
===================

Run HERO optimization algorithm


def _run_HERO(self):
====================

Run HERO algorithm for a single iteration/repeat ::

    >>> hero._stat_logger = ologger  # replace stat logger with a mock
    >>> hero._data = omatrix2  # replace data handler with another mock
    >>> hero._analyze_data()  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    Called OMatrix.analyze_data(
        <Mock ... SimInputDB>,
        <bound method HERO._add_info of 
        <simo.optimization.hero.HERO object at ...>>)
    True
    >>> hero.set_data(0)  # doctest: +ELLIPSIS
    Called OMatrix.construct_data(0)
    True
    >>> hero._run_HERO()  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    Called OMatrix.solution_feasibility(array([0, 0, 0, 0, 0]))
    Called OMatrix.solution_utility(array([0, 0, 0, 0, 0]))
    Called OMatrix.compare_utilities(None, 1.0)
    Called OMatrix.solution_feasibility(array([1, 0, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 0, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 0, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 0, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 2, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 2, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 3, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 3, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 4, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 4, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 0, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 0, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 1, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 1, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 1, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 1, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 2, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 2, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OLogger.add_round(array([1, 5, 2, 3, 0]), 1.0, 1.0)
    Called OMatrix.solution_feasibility(array([0, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([0, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 0, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 0, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 2, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 2, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 3, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 3, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 4, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 4, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 0, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 0, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 1, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 1, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 0, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 0, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 1, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 1, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 2, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 2, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OMatrix.solution_feasibility(array([1, 5, 2, 3, 0]))
    Called OMatrix.solution_utility(array([1, 5, 2, 3, 0]))
    Called OMatrix.compare_utilities(1.0, 1.0)
    Called OLogger.add_round(array([1, 5, 2, 3, 0]), 1.0, 1.0)