sparse_optimization.py 文件源码

def print_performance(self,Z,itr,Z_series=(1.,1.)):
        Yhat = self.get_Yhat(Z)
        fit = 1 - np.linalg.norm(self.Y - Yhat)**2/np.linalg.norm(self.Y)**2
        r2 = (1 - distance.correlation(self.Y.flatten(),Yhat.flatten()))**2
        print 'itr: %d, fit: %f, r2: %f, Z entropy: %f, Z min: %f, Z max: %f, Z change: %f' % (itr,fit,r2,
        np.average([np.exp(entropy(abs(z))) for z in Z.T]),Z.min(),Z.max(),
        np.linalg.norm(Z_series[-2] - Z_series[-1])/np.linalg.norm(Z_series[-2]))
        self.fit = (fit,r2)