2.3.2.1. Computing Wasserstein and Bottleneck Distances

[5]:

from ripser import ripser
from teaspoon.MakeData.PointCloud import Torus, Annulus
import numpy as np
from teaspoon.TDA.Distance import wassersteinDist, bottleneckDist
numPts = 500
seed = 0

# Generate Torus
t = Torus(N=numPts,seed = seed)

# Generate Annulus
a = Annulus(N=numPts,seed = seed)

# Compute persistence diagrams
PD1 = ripser(t,2)['dgms'][1]
PD2 = ripser(a,1)['dgms'][1]


[6]:

wassersteinDist(PD1,PD2,p=2,q=2)

[6]:

1.8922819954736267

[7]:

bottleneckDist(PD1, PD2, matching = True, plot = True)

[7]:

(0.6366934925317764,
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../_images/notebooks_distance_3_1.png