Exemple #1
0
def perpot_example(pp_args):
    weeks = 12
    goal = 0.3
    max_load = 1.0
    cycle_days = [
        u.WeekDays.monday, u.WeekDays.tuesday, u.WeekDays.wednesday,
        u.WeekDays.friday, u.WeekDays.saturday
    ]
    training_days = u.microcycle_days(cycle_days, weeks)
    training_days = u.filter_weeks(training_days, [3, 7, 11])
    # pp_args = params.pp_parms8
    print(pp_args)
    solution = differential_evolution(
        weeks,
        goal,
        training_days,
        POP_SIZE,
        max_load,
        pp_model.after_plan,
        # u.sort_loads,
        **pp_args)
    solution_fitness = u.fitness(solution, goal, GOOD_ENOUGH_THRES,
                                 pp_model.after_plan, **pp_args)
    perf_after_plan = pp_model.after_plan(solution, **pp_args)
    u.print_ea_result(solution, solution_fitness, perf_after_plan, goal)
    '''
def fitnessfatigue_example(ff_args):
    weeks = 12
    goal = 1.1 * ff_args["initial_p"]
    max_load = 150.0
    min_load = 0.0
    cycle_days = [u.WeekDays.monday, u.WeekDays.tuesday, u.WeekDays.wednesday, u.WeekDays.friday, u.WeekDays.saturday]
    training_days = u.microcycle_days(cycle_days, weeks)
    # training_days = u.filter_weeks(training_days, [3, 7, 11])
    # print(ff_args)
    solution = differential_evolution(
        weeks,
        goal,
        training_days,
        POP_SIZE,
        max_load,
        min_load,
        ff_model.after_plan,
        prequel_plan=[],
        pp_func=u.sort_loads,
        recomb_weight=0.7,
        scale_factor=0.8,
        pop_init_divisor=1,
        **ff_args
    )
    solution_fitness = u.fitness(solution, goal, GOOD_ENOUGH_THRES, ff_model.after_plan, **ff_args)
    perf_after_plan = ff_model.after_plan(solution, **ff_args)
    u.print_ea_result(solution, solution_fitness, perf_after_plan, goal)
Exemple #3
0
def fitnessfatigue_example(ff_args):
    weeks = 12
    goal = 1.1 * ff_args['initial_p']
    max_load = 150.0
    min_load = 0.0
    cycle_days = [
        u.WeekDays.monday, u.WeekDays.tuesday, u.WeekDays.wednesday,
        u.WeekDays.friday, u.WeekDays.saturday
    ]
    training_days = u.microcycle_days(cycle_days, weeks)
    # training_days = u.filter_weeks(training_days, [3, 7, 11])
    # print(ff_args)
    solution = differential_evolution(weeks,
                                      goal,
                                      training_days,
                                      POP_SIZE,
                                      max_load,
                                      min_load,
                                      ff_model.after_plan,
                                      prequel_plan=[],
                                      pp_func=u.sort_loads,
                                      recomb_weight=0.7,
                                      scale_factor=0.8,
                                      pop_init_divisor=1,
                                      **ff_args)
    solution_fitness = u.fitness(solution, goal, GOOD_ENOUGH_THRES,
                                 ff_model.after_plan, **ff_args)
    perf_after_plan = ff_model.after_plan(solution, **ff_args)
    u.print_ea_result(solution, solution_fitness, perf_after_plan, goal)
def perpot_example(pp_args):
    weeks = 12
    goal = 0.3
    max_load = 1.0
    cycle_days = [u.WeekDays.monday, u.WeekDays.tuesday, u.WeekDays.wednesday, u.WeekDays.friday, u.WeekDays.saturday]
    training_days = u.microcycle_days(cycle_days, weeks)
    training_days = u.filter_weeks(training_days, [3, 7, 11])
    # pp_args = params.pp_parms8
    print(pp_args)
    solution = differential_evolution(
        weeks,
        goal,
        training_days,
        POP_SIZE,
        max_load,
        pp_model.after_plan,
        # u.sort_loads,
        **pp_args
    )
    solution_fitness = u.fitness(solution, goal, GOOD_ENOUGH_THRES, pp_model.after_plan, **pp_args)
    perf_after_plan = pp_model.after_plan(solution, **pp_args)
    u.print_ea_result(solution, solution_fitness, perf_after_plan, goal)

    """