Persistence diagram and wasserstein distance using ripser vs torch_topological

[AmeerHamza96]

Hello,

1. I have used ripser and torch_topological libraries to compute cubical persistence of the same image but the two two diagrams are different.
2. About the wasserstein distance, I have tried to input same persistence diagram to persim.wasserstein and torch_topological.nn.wasserstein distance with same setting but the answers are different.

Can you please guide me what is the reason behind this? Am I doing something wrong? Is there a way to resolve this issue?

Ripser/Persim
"diagram1 = np.array([[0., 1.]])
diagram2 = np.array([[0., 1.],
[0., 1.]])
distance = persim.wasserstein(diagram2, diagram1)
output: Wasserstein distance: 0.7071067811865476"

with torch_topological
I got "tensor(0.5000)"

Thanks in advance.

[Pseudomanifold]

Please provide more information about the code you are using in torch_topological.