Comments (3)
I am not sure I understand your concern. I just tested expwin
and everything seems alright.
import numpy as np
from pygsp.filters import Expwin
from pygsp.graphs import Sensor
from matplotlib import pyplot as plt
N = 100
slope = 4
G = Sensor(N)
G.estimate_lmax()
f1 = filters.expwin.Expwin(G, band_min=None, band_max=0.4, slope=slope)
f2 = filters.expwin.Expwin(G, band_min=0.2, band_max=None, slope=slope)
f3 = filters.expwin.Expwin(G, band_min=0.2, band_max=0.4, slope=slope)
plt.figure(figsize=(15,4))
ax = plt.subplot(131)
f1.plot(ax=ax);
ax = plt.subplot(132)
f2.plot(ax=ax);
ax = plt.subplot(133)
f3.plot(ax=ax);
Please precise your concern.
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The function kernel_low pass is defined above taking the argument into account. I am closing the issue since this is not pygsp related.
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