images2gif.py 文件源码

def alterneigh(self, alpha, rad, i, b, g, r):
        if i-rad >= self.SPECIALS-1:
            lo = i-rad
            start = 0
        else:
            lo = self.SPECIALS-1
            start = (self.SPECIALS-1 - (i-rad))

        if i+rad <= self.NETSIZE:
            hi = i+rad
            end = rad*2-1
        else:
            hi = self.NETSIZE
            end = (self.NETSIZE - (i+rad))

        a = self.geta(alpha, rad)[start:end]

        p = self.network[lo+1:hi]
        p -= np.transpose(np.transpose(p - np.array([b, g, r])) * a)

    #def contest(self, b, g, r):
    #    """ Search for biased BGR values
    #            Finds closest neuron (min dist) and updates self.freq
    #            finds best neuron (min dist-self.bias) and returns position
    #            for frequently chosen neurons, self.freq[i] is high and self.bias[i] is negative
    #            self.bias[i] = self.GAMMA*((1/self.NETSIZE)-self.freq[i])"""
    #
    #    i, j = self.SPECIALS, self.NETSIZE
    #    dists = abs(self.network[i:j] - np.array([b,g,r])).sum(1)
    #    bestpos = i + np.argmin(dists)
    #    biasdists = dists - self.bias[i:j]
    #    bestbiaspos = i + np.argmin(biasdists)
    #    self.freq[i:j] -= self.BETA * self.freq[i:j]
    #    self.bias[i:j] += self.BETAGAMMA * self.freq[i:j]
    #    self.freq[bestpos] += self.BETA
    #    self.bias[bestpos] -= self.BETAGAMMA
    #    return bestbiaspos