Usignal

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

Bases: pylayers.signal.bsignal.Bsignal

Signal with an embedded uniform Base

This class inheritate from Bsignal. The only difference is that the x base is supposed to be uniform

Methods Summary

abs()	return the absolute value of an Usignal
alignc(u2)	align 2 Usignal
dx()	get the time step of Usignal.x
energy([axis])	calculate the energy of an Usignal
eprfl([axis])	Energy profile
expand(a)	expand the time support by a scale factor a
fftshift()
max()	maximum of Usignal
min()	minimum of Usignal
resample(x_new[, kind])	resample the Usignal with a new x base
setx(start, stop, dx)	set the x array of the Usignal (y=0)
truncate(imin, imax[, axis])	truncate USignal in range [posmin, posmax]
width()	get the extension support of the Usignal
window([win])	windowing Usignal Parameters ———-
zleft(xmin)	add zeros on the left until xmin
zlr(xmin, xmax)	add zeros to the left and to the right
zright(xmax)	add zeros on the right until xmax

Methods Documentation

abs()

return the absolute value of an Usignal

Usignal

alignc(u2)

align 2 Usignal

alignc <=> intersection alignc : align two Usignal on a same base

return a list which contains the two aligned signals

LUsignal

concatenated signal L1.y and L2.y

dx()

get the time step of Usignal.x

>>> from pylayers.signal.bsignal import *
>>> u = Usignal()
>>> u.setx(0,10,0.1)
>>> assert(u.dx()==0.1)

energy(axis=0)

calculate the energy of an Usignal

axisint

(default : 0)

energy : float

eprfl(axis=-1)

Energy profile

axis : int

if axis==0

$$delta_x sum_l |y(l,k)|^2$$

if axis==1

$$delta_x sum_k |y(l,k)|^2$$

cut

expand(a)

expand the time support by a scale factor a

afloat

expansion factor

Usignal : support extended signal

return a new Usignal with expanded factor a

fftshift()

max()

maximum of Usignal

m : maximum value of self.y

min()

minimum of Usignal

m : maximum value of self.y

resample(x_new, kind='linear')

resample the Usignal with a new x base

x_new needs to be strictly included in the original x base of the Usignal.

x is a 1D array y is a 2D array

if y is complex the interpolation is done on module and unwrapped phase separately

x_new : ndarray kind : string

‘linear’ |’spline’

setx(start, stop, dx)

set the x array of the Usignal (y=0)

start : float stop : float dx : float

>>> u = Usignal()
>>> u.setx(0,10,0.1)

truncate(imin, imax, axis=-1)

truncate USignal in range [posmin, posmax]

imin : int imax : int axis : axis to truncate (default -1)

Usignal

width()

get the extension support of the Usignal

width is conventionnaly equal to the difference between extremities + dx

w : float

window(win='hamming')

windowing Usignal Parameters ———-

winstring

window type (‘hamming’,’blackman’,’hanning’)

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from pylayers.signal.bsignal import *
>>> x = np.arange(2,8,0.1)
>>> y = np.ones(len(x))
>>> U = Usignal(x,y)
>>> fig,ax = U.plot()
>>> U.window('hamming')
>>> fig,ax = U.plot()

(Source code)

(png, hires.png, pdf)

(png, hires.png, pdf)

zleft(xmin)

add zeros on the left until xmin

xmin : float

zlr(xmin, xmax)

add zeros to the left and to the right

xminfloat

add zeros before xmin

xmaxfloat

add zeros after xmax

This corresponds to a gating between xmin and xmax

>>> from pylayers.signal.bsignal import *
>>> from matplotlib.pylab import *
>>> ip = TUsignal()
>>> ip.EnImpulse()
>>> f,a = ip.plot(typ=['v'])
>>> ip.zlr(-10,10)
>>> f,a = ip.plot(typ=['v'])

(Source code)

zright(xmax)

add zeros on the right until xmax

xmax : float