geneticalgorithm.py 文件源码

def FeCalc(self, Aoptimality=True):
        '''
        Compute estimation efficiency.

        :param Aoptimality: Kind of optimality to optimize, A- or D-optimality
        :type Aoptimality: boolean
        '''
        try:
            invM = scipy.linalg.inv(self.X)
        except scipy.linalg.LinAlgError:
            try:
                invM = scipy.linalg.pinv(self.X)
            except np.linalg.linalg.LinAlgError:
                invM = np.nan
        sys.exc_clear()
        invM = np.array(invM)
        st1 = np.dot(self.CX, invM)
        CMC = np.dot(st1, t(self.CX))
        if Aoptimality == True:
            self.Fe = float(self.CX.shape[0] / np.matrix.trace(CMC))
        else:
            self.Fe = float(np.linalg.det(CMC)**(-1 / len(self.C)))
        self.Fe = self.Fe / self.experiment.FeMax
        return self