elsim.py 文件源码

def __init__(self, x, ys):
        import numpy as np
        from sklearn.neighbors import NearestNeighbors
        #print x, ys

        CI = np.array( [x.checksum.get_signature_entropy(), x.checksum.get_entropy()] )
        #print CI, x.get_info()
        #print

        for i in ys:
            CI = np.vstack( (CI, [i.checksum.get_signature_entropy(), i.checksum.get_entropy()]) )

        #idx = 0
        #for i in np.array(CI)[1:]:
        #    print idx+1, i, ys[idx].get_info()
        #    idx += 1

        self.neigh = NearestNeighbors(2, 0.4)
        self.neigh.fit(np.array(CI))
        #print self.neigh.kneighbors( CI[0], len(CI) )

        self.CI = CI
        self.ys = ys