statistics.py 文件源码

def get_rv(self,signal):

        #extract parameters
        N,p=signal.H1.shape

        if self.type=="PFA":

            if self.detector.estimate_sigma2==True:
                rv=f(p,s-p)
            else:
                rv=chi2(p)

        if self.type=="PD":

            H1=np.matrix(signal.H1)
            x1=np.matrix(signal.x1).T
            H2=np.matrix(signal.H2)
            x2=np.matrix(signal.x2).T
            sigma2=signal.sigma2

            #compute non central parameter
            PH2_perp=np.eye(H2.shape[0])-H2*lg.inv(H2.T*H2)*H2.T
            y=H1*x1
            nc=y.T*PH2_perp*y/sigma2
            nc=min(np.asscalar(nc),self.nc_max)

            if self.detector.estimate_sigma2==True:
                N,t=H2.shape
                s=N-t
                rv=ncf(p,s-p,nc)
            else:
                rv=ncx2(p,nc)

        return rv