dsp/lib/sweeps.py
2015-10-18 23:06:39 -07:00

54 lines
1.6 KiB
Python

from . import tau
import numpy as np
def sweep(amp, length, begin=20, end=20480, method='linear'):
method = method or 'linear'
xs = np.arange(length)/length
if method in ('linear', 'quadratic', 'logarithmic', 'hyperbolic'):
ys = amp*sig.chirp(xs, begin, 1, end, method=method)
elif method is 'sinesweep':
ang = lambda f: tau*f
# because xs ranges from 0:1, length is 1 and has been simplified out
domain = np.log(ang(end)/ang(begin))
ys = amp*np.sin(ang(begin)/domain*(np.exp(xs*domain) - 1))
return ys
def tsp(N, m=0.5):
"""
OATSP(Optimized Aoshima's Time-Stretched Pulse) generator
x = tsp( N, m )
N : length of the time-stretched pulse
m : ratio of the swept sine (0 < m < 1)
Author(s): Seigo UTO 8-23-95
Reference:
Yoiti SUZUKI, Futoshi ASANO, Hack-Yoon KIM and Toshio SONE,
"Considerations on the Design of Time-Stretched Pulses,"
Techical Report of IEICE, EA92-86(1992-12)
"""
# http://www.sound.sie.dendai.ac.jp/dsp/e-21.html
if m < 0 or m > 1:
raise Exception("sdfgsdfgsdg")
if N < 0:
raise Exception("The number of length must be the positive number")
NN = 2**np.floor(np.log2(N)) # nearest
NN2 = NN//2
M = np.round(NN2*m)
nn2 = np.arange(NN2 + 1)**2
j = np.complex(0, 1)
H = np.exp(j*4*M*np.pi*nn2/NN**2)
H2 = np.hstack([H, np.conj(H[1:NN2][::-1])])
x = np.fft.ifft(H2)
x = np.hstack([x[NN2 - M:NN + 1], x[0:NN2 - M + 1]])
x = np.hstack([x.real, np.zeros(1, N - NN)])
return x