TBsignal

class pylayers.signal.bsignal.TBsignal(x=array([], dtype=float64), y=array([], dtype=float64), label=[])

Bases: pylayers.signal.bsignal.Bsignal

Based signal in Time domain

Methods Summary

b2tu(N)	conversion from TBsignal to TUsignal
b2tu2(fsGHz, Tobsns)	conversion from TBsignal to TUsignal
integ(Tns[, Tsns])	integation of alphak tauk of TBsignal
plot(**kwargs)	plot TBsignal
tap(fcGHz, WGHz, Ntap)	Back to baseband
translate(tau)	translate TBsignal signal by tau

Methods Documentation

b2tu(N)

conversion from TBsignal to TUsignal

Ninteger

Number of points

U : TUsignal

This function exploits linear interp1d

>>> from pylayers.signal.bsignal import *
>>> import matplotlib.pyplot as plt
>>> x = np.array( [ 1, 3 , 6 , 11 , 18])
>>> y = np.array( [ 0,1 ,-5, 8 , 10])
>>> sb = TBsignal(x,y)
>>> su20 = sb.b2tu(20)
>>> su100 = sb.b2tu(100)
>>> fi = plt.figure()
>>> st = sb.stem()
>>> fig,ax = su20.plot(color='k')
>>> fig,ax = su100.plot(color='r')
>>> ti = plt.title('b2tu : sb(blue) su20(black) su200(red)')

(Source code)

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b2tu2(fsGHz, Tobsns)

conversion from TBsignal to TUsignal

Ninteger

Number of points

U : TUsignal

This function exploits linear interp1d

>>> from pylayers.signal.bsignal import *
>>> import matplotlib.pyplot as plt
>>> x = np.array( [ 1, 3 , 6 , 11 , 18])
>>> y = np.array( [ 0,1 ,-5, 8 , 10])
>>> sb = TBsignal(x,y)
>>> su20 = sb.b2tu(20)
>>> su100 = sb.b2tu(100)
>>> fi = plt.figure()
>>> st = sb.stem()
>>> fig,ax = su20.plot(color='k')
>>> fig,ax = su100.plot(color='r')
>>> ti = plt.title('b2tu : sb(blue) su20(black) su200(red)')

(Source code)

(png, hires.png, pdf)

(png, hires.png, pdf)

(png, hires.png, pdf)

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integ(Tns, Tsns=50)

integation of alphak tauk of TBsignal

used energy detector for IEEE 802.15.6 standard

Tns : Tsns :

plot(**kwargs)

plot TBsignal

unit1 : actual unit of data unit2 : unit for display dist : boolean xmin : float xmax : float logx : boolean logy :boolean

>>> import numpy as np
>>> from pylayers.signal.bsignal import *
>>> from matplotlib.pylab import *
>>> x = np.array( [ 1, 3 , 6 , 11 , 18])
>>> y = np.array( [ 0,1 ,-5, 8 , 10])
>>> s = Bsignal(x,y)
>>> fi = figure()
>>> fig,ax=s.plot(typ=['v'])
>>> ti = title('TBsignal : plot')
>>> show()

tap(fcGHz, WGHz, Ntap)

Back to baseband

fcGHzfloat

center frequency

WGHzfloat

bandwidth

Ntapint

Number of tap

Implement formula (2.52) from D.Tse book page 50

translate(tau)

translate TBsignal signal by tau

taufloat

delay for translation

Once translated original signal and translated signal might not be on the same grid

>>> from pylayers.signal.bsignal import *
>>> from matplotlib.pylab import *
>>> ip = TUsignal()
>>> ip.EnImpulse()
>>> ip.translate(-10)
>>> fig,ax=ip.plot(typ=['v'])
>>> show()

(Source code)