3d5e54b8d683ab0a18210b8d27add5fa35dcb81d,acoular/fbeamform.py,BeamformerFunctional,calc,#BeamformerFunctional#Any#Any#,422

Before Change

           
        kj = 2j*pi*self.freq_data.fftfreq()/self.c
        steerVecFormulation = steerVecTranslation(self.steer)
        nMics = float(self.freq_data.numchannels)
        if self.r_diag:
            normFactor = sqrt(1.0 / (nMics * nMics - nMics))
        elif not self.r_diag:
            normFactor = 1.0 / nMics
        for i in self.freq_data.indices:        
            if not fr[i]:

After Change

                    fill_diagonal(csm, 0)
                    csmRoot = fractional_matrix_power(csm, 1.0 / self.gamma)
                    beamformerOutput, steerNorm = beamformerFreq(False, steerVecFormulation, False, 1.0, (self.r0, self.rm, kji, csmRoot[newaxis]))
                    beamformerOutput /= steerNorm  // take normalized steering vec
                    
                    // set (unphysical) negative output values to 0
                    indNegSign = sign(beamformerOutput) < 0
                    beamformerOutput[indNegSign] = 0.0
                else:
                    eva = array(self.freq_data.eva[i][newaxis], dtype="float64") ** (1.0 / self.gamma)
                    eve = array(self.freq_data.eve[i][newaxis], dtype="complex128")
                    beamformerOutput, steerNorm = beamformerFreq(True, steerVecFormulation, self.r_diag, 1.0, (self.r0, self.rm, kji, eva, eve))  // takes all EigVal into account
                    beamformerOutput /= steerNorm  // take normalized steering vec
                ac[i] = (beamformerOutput ** self.gamma) * steerNorm * normFactor  // the normalization must be done outside the beamformer
                fr[i] = True
            

Instances