(guebin) Bunny (2)

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from pygsp import graphs, filters, plotting, utils
import plotly.express as px
from IPython.display import HTML

G = graphs.Bunny()
n = G.N

g = filters.Heat(G, tau=80) # 꼬리부분의 빨간신호를 퍼지게하는 정도

normal = np.random.randn(n)*0.3
unif = np.concatenate([np.random.rand(63)*3, np.zeros(n-63)]); np.random.shuffle(unif)
noise = normal + unif 
plt.plot(noise); plt.plot(unif)

[<matplotlib.lines.Line2D at 0x7f7528359490>]

f = np.zeros(n)
f[1000] = 3234
f = g.filter(f, method='chebyshev') 

2022-08-16 19:14:48,206:[WARNING](pygsp.graphs.graph.lmax): The largest eigenvalue G.lmax is not available, we need to estimate it. Explicitly call G.estimate_lmax() or G.compute_fourier_basis() once beforehand to suppress the warning.

plt.plot(f)

[<matplotlib.lines.Line2D at 0x7f752813a950>]

W = G.W.toarray()
x = G.coords[:,0]
y = G.coords[:,1]
z = G.coords[:,2]

#                     color=f,
#                     opacity=0.7,
#                     height=400,
#                     size=abs(f+noise),
#                     range_color=[-1,5],
#                     color_continuous_scale='jet')
# fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
# fig.update_traces(marker=dict(line=dict(width=0)))
# HTML(fig.to_html(include_mathjax=False, config=dict({'scrollZoom':False})))

#                     color=f+noise,
#                     opacity=1,
#                     height=400,
#                     size=abs(f+noise),
#                     range_color=[-1,5],
#                     color_continuous_scale='jet')
# fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
# fig.update_traces(marker=dict(line=dict(width=0)))
# HTML(fig.to_html(include_mathjax=False, config=dict({'scrollZoom':False})))