HSICTestObject.py 文件源码

def compute_induced_kernel_matrix_on_data(self,data_x,data_y):
        '''Z follows the same distribution as X; W follows that of Y.
        The current data generating methods we use 
        generate X and Y at the same time. '''
        size_induced_set = max(self.num_inducex,self.num_inducey)
        #print "size_induce_set", size_induced_set
        if self.data_generator is None:
            subsample_idx = np.random.randint(self.num_samples, size=size_induced_set)
            self.data_z = data_x[subsample_idx,:]
            self.data_w = data_y[subsample_idx,:]
        else:
            self.data_z, self.data_w = self.data_generator(size_induced_set)
            self.data_z[[range(self.num_inducex)],:]
            self.data_w[[range(self.num_inducey)],:]
        print 'Induce Set'
        if self.kernelX_use_median:
            sigmax = self.kernelX.get_sigma_median_heuristic(data_x)
            self.kernelX.set_width(float(sigmax))
        if self.kernelY_use_median:
            sigmay = self.kernelY.get_sigma_median_heuristic(data_y)
            self.kernelY.set_width(float(sigmay))
        Kxz = self.kernelX.kernel(data_x,self.data_z)
        Kzz = self.kernelX.kernel(self.data_z)
        #R = inv(sqrtm(Kzz))
        R = inv(sqrtm(Kzz + np.eye(np.shape(Kzz)[0])*10**(-6)))
        phix = Kxz.dot(R)
        Kyw = self.kernelY.kernel(data_y,self.data_w)
        Kww = self.kernelY.kernel(self.data_w)
        #S = inv(sqrtm(Kww))
        S = inv(sqrtm(Kww + np.eye(np.shape(Kww)[0])*10**(-6)))
        phiy = Kyw.dot(S)
        return phix, phiy