Bsignal

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

Bases: pylayers.util.project.PyLayers

Signal with an embedded time base

This class gathers a 1D signal and its axis indexation.

The x base is not necessarily uniform

x has 1 axis

x and the last axes of y have the same length

By construction shape(y)[-1] :=len(x), len(x) takes priority in case of observed conflict

Methods Summary

append(bs)	append bs to Bsignal
cformat(**kwargs)	complex format
extract(u)	extract a subset of signal from index
flatteny([yrange, reversible])	flatten y array
gating(xmin, xmax)	gating between xmin and xmax
imshow(**kwargs)	imshow of y matrix
len()	returm length of x axis
load(filename)	load a Bsignal from a Matlab File
max()	max value of the signal (module if complex)
mean()	mean value of the signal
min()	min value of the signal (module if complex)
plot(**kwargs)	plot signal Bsignal
save(filename)	save Bsignal in Matlab File Format
setx(x)	setx : set x vector
sety(fun)	sety : set y vector
stem(**kwargs)	stem display
step([color])	plot steps display

Methods Documentation

append(bs)

append bs to Bsignal

cformat(**kwargs)

complex format

saxlist

selected output axis from y default [0,1] typ : string ‘m’ : modulus ‘v’ : value ‘l10’ : dB (10 log10) ‘l20’ : dB (20 log10) ‘d’ : phase degrees ‘r’ : phase radians ‘du’ : phase degrees unwrap ‘ru’ : phase radians unwrap ‘gdn’ : group delay (ns) ‘gdm’ : group distance (m) ‘re’ : real part ‘im’ : imaginary part

sellist of ndarray()

data selection along selected axis, all the axis void default [[],[]]

ik : fixed axis value default (0)

a0first data axis

this axis can be self.x or not

a1 : second data axis dt : data

ylabelsstring

label for the selected complex data format

This function returns 2 arrays x and y and the corresponding labels Convention : the last axis of y has same dimension as x y can have an arbitrary number of axis i.e a MIMO channel matrix could be x : f and y : t x r x f

>>> import numpy as np
>>> S = Bsignal()
>>> x = np.arange(100)
>>> y = np.arange(400).reshape(2,2,100)+1j*np.arange(400).reshape(2,2,100)
>>> S.x = x
>>> S.y = y
>>> S.cformat()
(array([[-240.        ,   43.01029996],
       [  49.03089987,   52.55272505]]), 'Magnitude (dB)')

extract(u)

extract a subset of signal from index

u : np.array

O : Usignal

>>> from pylayers.signal.bsignal import *
>>> import numpy as np
>>> x = np.arange(0,1,0.01)
>>> y = np.sin(2*np.pi*x)
>>> s = Bsignal(x,y)
>>> su = s.extract(np.arange(4,20))
>>> f,a = s.plot()
>>> f,a = su.plot()

(Source code)

(png, hires.png, pdf)

(png, hires.png, pdf)

flatteny(yrange=[], reversible=False)

flatten y array

yrange : array of y index values to be flattenned reversible : boolean

if True the sum is place in object member yf else y is smashed

gating(xmin, xmax)

gating between xmin and xmax

xmin : float xmax : float

nothing self is modified

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from pylayers.signal.bsignal import *
>>> x = np.linspace(-10,10,100)
>>> y = np.sin(2*np.pi*12*x)+np.random.normal(0,0.1,len(x))
>>> s = TUsignal(x,y)
>>> fig,ax = s.plot(typ=['v'])
>>> txt1 = plt.title('before gating')
>>> plt.show()

(Source code, png, hires.png, pdf)

>>> s.gating(-3,4)
>>> fig,ax=s.plot(typ=['v'])
>>> txt2 = plt.title('after gating')
>>> plt.show()

(png, hires.png, pdf)

When a gating is applied the removed information is lost

imshow(**kwargs)

imshow of y matrix

interpolationstring

‘none’|’nearest’|’bilinear’

cmapcolormap

plt.cm.jet

aspectstring

‘auto’ (default) ,’equal’,’scalar’

functionstring

{‘imshow’|’pcolormesh’}

typstring

‘l20’,’l10’

vmin : min value vmax : max value sax : list

select axe

bindex

>>> f = np.arange(100)
>>> y = np.random.randn(50,100)+1j*np.random.randn(50,100)
>>> F = FUsignal(f,y)

len()

returm length of x axis

load(filename)

load a Bsignal from a Matlab File

filename : string

Bsignal.save

max()

max value of the signal (module if complex)

mean()

mean value of the signal

min()

min value of the signal (module if complex)

plot(**kwargs)

plot signal Bsignal

iy : index of the waveform to plot (-1 = all) col : string

default ‘black’

vline : ndarray hline : ndarray unit1 : string

default ‘V’

unit2string

default ‘V’

xmin : float xmax : float ax : axes instance or [] dB : boolean

default False

distboolean

default False

displayboolean

default True

logxboolean

defaut False

logyboolean

default False

fig : figure ax : np.array of axes

pylayers.util.plotutil.mulcplot

save(filename)

save Bsignal in Matlab File Format

filename : string

>>> from pylayers.signal.bsignal import *
>>> import matplotlib.pyplot as plt
>>> e = TUsignal()
>>> e.EnImpulse(feGHz=100)
>>> fig,ax = e.plot(typ=['v'])
>>> tit1 = plt.title('original waveform')
>>> e.save('impulse.mat')
>>> del e
>>> h = TUsignal()
>>> h.load('impulse.mat')
>>> fig,ax = h.plot(typ=['v'])
>>> tit2 = plt.title('retrieved waveform')

(Source code)

(png, hires.png, pdf)

(png, hires.png, pdf)

Bsignal.load

setx(x)

setx : set x vector

x : np.array

y is set to a zero vector

Use __set__ instead

sety(fun)

sety : set y vector

fun : function

stem(**kwargs)

stem display

colorstring

default ‘b-‘

>>> from pylayers.signal.bsignal import *
>>> import matplotlib.pyplot as plt
>>> si = Bsignal()
>>> si.x= np.arange(100)
>>> si.y= np.arange(100)[None,:]
>>> f,a = si.stem()

(Source code)

step(color='b')

plot steps display

colorstring

default ‘b-‘