def __init__(self, N, gen_size, data):
self.N = N
self.gen_size = gen_size
self.f = SharpeV2(data, 1.0)
self.f2 = Sharpe(data, 1.0)
self.state = []
def __init__(self, lambda_, gen_size, data):
self.lambda_ = lambda_
self.gen_size = gen_size
self.operators = [FloatMutation, Crossover]
self.f = Sharpe(data, 1.0)
self.state = []
def __init__(self, lambda_, gen_size, data):
self.lambda_ = lambda_
self.gen_size = gen_size
self.tau = 1 / 3
self.d = np.sqrt(gen_size)
self.d_i = gen_size
self.f = Sharpe(data, 1.0)
self.state = []
def __init__(self, lambda_, gen_size, data):
self.n = np.random.randint(100)
self.lambda_ = lambda_
self.mu = int(np.ceil(lambda_ / 4))
self.tau = 1 / np.sqrt(self.n)
self.tau_i = 1 / (np.sqrt(self.n)**0.25)
self.f = Sharpe(data, 1.0)
self.gen_size = gen_size
self.state = []
def __init__(self, lambda_, sa, gen_size, data):
self.lambda_ = lambda_
self.gen_size = gen_size
self.f = Sharpe(data, 1.0)
self.state = []
self.sa = sa
def __init__(self, subspecies_number, data, algorithm):
self.subspecies_number = subspecies_number
self.data = data
self.algorithm = algorithm
self.f = Sharpe(data, 1.0)