61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
from . import xsp
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import numpy as np
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def smoothfft(xs, ys, bw=1, precision=512):
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"""performs log-lin smoothing on magnitude data,
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generally from the output of averfft."""
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# TODO: option to extrapolate (pad) fft data
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xs2 = xsp(precision)
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ys2 = np.zeros(precision)
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log_xs = np.log(xs)
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for i, x in enumerate(xs2):
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dist = np.exp(np.abs(log_xs - np.log(x + 1e-35)))
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window = np.maximum(0, 1 - (dist - bw))
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# at this point you could probably
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# normalize our *triangular* window to 0-1
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# and transform it into *another* windowing function
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wsum = np.sum(window)
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ys2[i] = np.sum(ys*window/wsum)
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return xs2, ys2
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def smoothfft2(xs, ys, bw=1, precision=512, compensate=True):
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"""performs log-lin smoothing on magnitude data,
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generally from the output of averfft."""
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xs2 = xsp(precision)
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ys2 = np.zeros(precision)
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log2_xs2 = np.log2(xs2)
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for i, x in enumerate(xs):
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#dist = np.abs(np.log2(xs2/(x + 1e-35)))/bw
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dist = np.abs(log2_xs2 - np.log2(x + 1e-35))/bw
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#window = np.maximum(0, 1 - dist) # triangle window
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window = np.exp(-dist**2/(0.5/2)) # gaussian function (non-truncated)
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ys2 += ys[i]*window
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if compensate:
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_, temp = smoothfft2(xs, np.ones(len(xs)), bw=bw, precision=precision, compensate=False)
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ys2 /= temp
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return xs2, ys2
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def smoothfft3(xs, ys, bw=1, precision=1024):
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# actually this will never work...
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# you need to go back to smoothfft2,
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# which technically works as-designed,
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# and fix the compensation to work with widely-spaced data.
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raise Exception("smoothfft3 is broken.")
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xs2 = xsp(precision)
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ys2 = np.zeros(precision)
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step = (xs[1] - xs[0])
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if True:
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for i, x in enumerate(xs):
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dist = np.abs(xs2 - x)
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bw2 = x*bw/2
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window = np.maximum(0, 1 - dist/bw2)
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#window = np.minimum(1, np.maximum(0, 1 - (dist - bw)))
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ys2 += ys[i]*window
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else:
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for i, x2 in enumerate(xs2):
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dist = np.abs(xs - x2)
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window = np.maximum(0, 1 - (dist/step/bw))
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wsum = np.sum(window)
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ys2[i] = np.sum(ys*window/wsum)
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return xs2, ys2
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