kernels.py 文件源码

def deriveKernel(self, params, i):
        self.checkParamsI(params, i)

        #find the relevant W
        numSNPs = self.X_scaled.shape[1]
        unitNum = i / numSNPs
        weightNum = i % numSNPs

        nnX_unitNum = self.applyNN(self.X_scaled, params, unitNum) / float(self.numUnits)
        w_deriv_relu = self.X_scaled[:, weightNum].copy()
        w_deriv_relu[nnX_unitNum <= 0] = 0

        K_deriv1 = np.outer(nnX_unitNum, w_deriv_relu)
        K_deriv = K_deriv1 + K_deriv1.T
        return K_deriv