def filter_gaussian(Ys,sigma,plotToo=False):
    """simple gaussian convolution. Returns same # of points as gotten."""
    timeA=time.time()
    window=scipy.signal.gaussian(len(Ys),sigma)
    window/=sum(window)
    Ys2=np.convolve(Ys,window,'same')
    print("LEN:",len(Ys2),len(Ys))
    timeB=time.time()
    print("convolution took %.03f ms"%((timeB-timeA)*1000))
    if len(Ys2)!=len(Ys):
        print("?!?!?!? convolution point size mismatch")
    if plotToo:
        pylab.plot(Ys,label='original',alpha=.2)
        pylab.plot(Ys2,'b-',label='smooth')
        pylab.legend()
        pylab.show()
    return Ys2
def filter_gaussian(Ys,sigma,plotToo=False):
    """simple gaussian convolution. Returns same # of points as gotten."""
    timeA=time.time()
    window=scipy.signal.gaussian(len(Ys),sigma)
    window/=sum(window)
    Ys2=np.convolve(Ys,window,'same')
    print("LEN:",len(Ys2),len(Ys))
    timeB=time.time()
    print("convolution took %.03f ms"%((timeB-timeA)*1000))
    if len(Ys2)!=len(Ys):
        print("?!?!?!? convolution point size mismatch")
    if plotToo:
        pylab.plot(Ys,label='original',alpha=.2)
        pylab.plot(Ys2,'b-',label='smooth')
        pylab.legend()
        pylab.show()
    return Ys2
def filter_gaussian ( Ys , sigma , plotToo = False ) : timeA = time . time ( ) window = scipy . signal . gaussian ( len ( Ys ) , sigma ) window /= sum ( window ) Ys2 = np . convolve ( Ys , window , 'same' ) print ( "LEN:" , len ( Ys2 ) , len ( Ys ) ) timeB = time . time ( ) print ( "convolution took %.03f ms" % ( ( timeB - timeA ) * 1000 ) ) if len ( Ys2 ) != len ( Ys ) : print ( "?!?!?!? convolution point size mismatch" ) if plotToo : pylab . plot ( Ys , label = 'original' , alpha = .2 ) pylab . plot ( Ys2 , 'b-' , label = 'smooth' ) pylab . legend ( ) pylab . show ( ) return Ys2
simple gaussian convolution. Returns same # of points as gotten.
simple gaussian convolution . Returns same # of points as gotten .