

def __init__(self, numOGaus=10, alphaA=0.02, alphaM=0.02, alphaS=0.02):
    self.alphaA = alphaA
    self.alphaM = alphaM
    self.alphaS = alphaS
    self.minSig = 1e-06
    self.numOGaus = numOGaus
    self.rangeMin = (- 20.0)
    self.rangeMax = 20.0
    self.epsilon = ((self.rangeMax - self.rangeMin) / (sqrt(2.0) * float((self.numOGaus - 1))))
    self.propFakt = (1.0 / float(self.numOGaus))
    self.distFakt = (1.0 / float((self.numOGaus - 1)))
    self.distRange = (self.rangeMax - self.rangeMin)
    self.sigma = ones(self.numOGaus)
    self.mue = zeros(self.numOGaus)
    self.alpha = ones(self.numOGaus)
    self.sigma *= self.epsilon
    self.alpha /= float(self.numOGaus)
    for i in range(self.numOGaus):
        self.mue[i] = (((self.distRange * float(i)) * self.distFakt) + self.rangeMin)
    self.baseline = 0.0
    self.best = 1e-06

dataset/ETHPy150Open pybrain/pybrain/pybrain/tools/mixtures/mogpuremax.py MixtureOfGaussians.__init__/original