Example #1
0
 def eval(self, **kwrgs):
     """
     """
     for kt in range(Nb_tx):
         tx = np.array([
             self.tx.position[0, kt + 1], self.tx.position[1, kt + 1],
             self.tx.position[2, kt + 1]
         ])
         link.a = tx
         for kr in range(Nb_Run):
             rx = np.array([
                 S.rx.position[0, Run], S.rx.position[1, Run],
                 S.rx.position[2, Run]
             ])
             link.b = rx
             tic = time.clock()
             ak, tk = link.eval(verbose=False, diffraction=True)
             toc = time.clock()
             ciro = link.H.applywav(wav.sfg)
             cir = bs.TUsignal(ciro.x, np.squeeze(np.sum(ciro.y, axis=0)))
             tac = time.clock()
             tcir[Run] = cir
             print toc - tic, tac - toc
Example #2
0
    def ref156(self, beta=0.5):
        """ reference pulse of IEEE 802.15.6 UWB standard

        Parameters
        ----------

        beta : float 
            roll-off factor
        Tns = 1/499.2MHz

        Notes
        -----

        From P8O2.15.6/D02 December 2010  Formula 96 p 215

        """
        Tw = self['twns']
        fe = self['feGHz']
        te = 1. / fe
        beta = 0.5
        Tns = 1. / 0.4992
        x = np.linspace(-0.5 * Tw + te / 2,
                        0.5 * Tw + te / 2,
                        Np,
                        endpoint=False)
        z = x / Tns
        t1 = np.sin(np.pi * (1 - beta) * z)
        t2 = np.cos(np.pi * (1 + beta) * z)
        t3 = (np.pi * z) * (1 - (4 * beta * z)**2)
        y = (t1 + 4 * beta * z * t2) / t3

        st = bs.TUsignal()
        st.x = x
        st.y = y
        sf = st.ftshift()

        return (st, sf)
Example #3
0
    def ip_generic(self):
        """ Create an energy normalized Gaussian impulse (Usignal)

        ip_generic(self,parameters)


        """
        Tw = self['twns']
        fcGHz = self['fcGHz']
        WGHz = self['WGHz']
        thresh = self['threshdB']
        feGHz = self['feGHz']
        te = 1.0 / feGHz

        self['te'] = te
        Np = feGHz * Tw
        self['Np'] = Np
        #x      = np.linspace(-0.5*Tw+te/2,0.5*Tw+te/2,Np,endpoint=False)
        #x     = arange(-Tw,Tw,te)
        w = bs.TUsignal()
        w.EnImpulse(fcGHz=fcGHz, WGHz=WGHz, threshdB=thresh, feGHz=feGHz)
        #W = w.ft()
        W = w.ft()
        return (w, W)
Example #4
0
    def pltcir(self,
               itx=1,
               irx=1,
               mode='linear',
               noise=False,
               color='b',
               format='a',
               fig=[],
               ax=[]):
        """ plot Channel Impulse Response

        Parameters
        ----------

        itx : Tx index
        irx : Rx index
        mode : str
            {'linear','dB'}
            noise : boolean
        color : string
            default 'b'

        >>> from pylayers.simul.simulem import *
        >>> S = Simul()
        >>> S.load('where2.ini')
        >>> S.run(1,1)
        >>> S.pltcir(1,1,mode='linear',noise=False,color='k')

        """

        if fig == []:
            fig = plt.gcf()
        #if ax==[]:
        #    ax = fig.gca()

        _filecir = self.dcir[itx][irx] + '.mat'
        filecir = pyu.getlong(_filecir,
                              pstruc['DIRCIR'] + '/Tx' + str('%0.3d' % itx))
        D = spio.loadmat(filecir)
        ax = fig.add_subplot('211')

        fig, ax = self.show(itx, irx, fig=fig, ax=ax)
        ax = fig.add_subplot('212')
        if 'a' in format:
            kxa = 't'
            kya = 'cir'
            ta = D[kxa]
            Tobs = ta[-1] - ta[0]
            te = ta[1] - ta[0]
            if noise:
                na = bs.Noise(Tobs + te, 1. / te)
                naf = na.gating(4.493, 0.5)
            cira = bs.TUsignal(ta, D[kya][:, 0])

        if 'o' in format:
            kxo = 'to' + str(irx)
            kyo = 'ciro' + str(irx)
            to = D[kxo]
            Tobs = to[-1] - to[0]
            te = to[1] - to[0]
            if noise:
                no = bs.Noise(Tobs + te, 1. / te)
                nof = no.gating(4.493, 0.5)
            ciro = bs.TUsignal(to, D[kyo][:, 0])

        if mode == 'linear':
            #plt.plot(ta,naf.y,color='k',label='Noise')
            plt.plot(ta, D[kya], label='Rx ' + str(irx), color=color)
            plt.xlabel('Time (ns)')
            '''if noise:
                naf.plot(col='k')
            cira.plot(col=color)'''
        else:
            '''if noise:
                naf.plotdB(col='k')
            cira.plotdB()'''
            plt.plot(ta,
                     20 * np.log10(abs(D[kya])),
                     label='Rx ' + str(irx),
                     color=color)
            plt.xlabel('Time (ns)')


#        plt.legend()
        plt.show()