100 lines
2.5 KiB
Python
100 lines
2.5 KiB
Python
import numpy as np
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def _deco_win(f):
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# gives scipy compatibility
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def deco(N, *args, sym=True, **kwargs):
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if N < 1:
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return np.array([])
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if N == 1:
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return np.ones(1)
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odd = N % 2
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if not sym and not odd:
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N = N + 1
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w = f(N, *args, **kwargs)
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if not sym and not odd:
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return w[:-1]
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return w
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return deco
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def _gen_hamming(*a):
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L = len(a)
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a += (0, 0, 0, 0, 0) # pad so orders definition doesn't error
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orders = [
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lambda fac: 0,
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lambda fac: a[0],
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lambda fac: a[0] - a[1]*np.cos(1*fac),
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lambda fac: a[0] - a[1]*np.cos(1*fac) + a[2]*np.cos(2*fac),
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lambda fac: a[0] - a[1]*np.cos(1*fac) + a[2]*np.cos(2*fac)
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- a[3]*np.cos(3*fac),
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lambda fac: a[0] - a[1]*np.cos(1*fac) + a[2]*np.cos(2*fac)
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- a[3]*np.cos(3*fac) + a[4]*np.cos(4*fac),
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]
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f = orders[L]
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return lambda N: f(np.arange(0, N)*2*np.pi/(N - 1))
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def _normalize(*args):
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a = np.asfarray(args)
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return a/np.sum(a)
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def _h(*args):
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return _deco_win(_gen_hamming(*args))
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blackman_inexact = _h(0.42, 0.5, 0.08)
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blackman = _h(0.42659, 0.49656, 0.076849)
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blackman_nuttall = _h(0.3635819, 0.4891775, 0.1365995, 0.0106411)
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blackman_harris = _h(0.35875, 0.48829, 0.14128, 0.01168)
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nuttall = _h(0.355768, 0.487396, 0.144232, 0.012604)
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flattop = _h(*_normalize(1, 1.93, 1.29, 0.388, 0.028)) # FTSRS
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# flattop_weird = _h(*_normalize(1, 1.93, 1.29, 0.388, 0.032)) # ??? wtf
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flattop_weird = _h(0.2156, 0.4160, 0.2781, 0.0836, 0.0069) # ??? scipy crap
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hann = _h(0.5, 0.5)
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hamming_inexact = _h(0.54, 0.46)
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hamming = _h(0.53836, 0.46164)
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@_deco_win
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def triangular(N):
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if N % 2 == 0:
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return 1 - np.abs((2*np.arange(N) + 1)/N - 1)
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else:
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return 1 - np.abs(2*(np.arange(N) + 1)/(N + 1) - 1)
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@_deco_win
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def parzen(N):
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odd = N % 2
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n = np.arange(N/2)
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if not odd:
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n += 0.5
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center = 1 - 6*(2*n/N)**2*(1 - 2*n/N)
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outer = 2*(1 - 2*n/N)**3
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center = center[:len(center)//2]
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outer = outer[len(outer)//2:]
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if not odd:
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return np.r_[outer[::-1], center[::-1], center, outer]
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else:
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return np.r_[outer[::-1], center[::-1], center[1:], outer]
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@_deco_win
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def cosine(N):
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return np.sin(np.pi*(np.arange(N) + 0.5)/N)
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@_deco_win
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def welch(N):
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return 1 - (2*np.arange(N)/(N - 1) - 1)**2
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# TODO: rename or something
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@_deco_win
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def sinc(N):
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return np.sinc((np.arange(N) - (N - 1)/2)/2)
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