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Riemannian Measure μ ? #24

@Noeloikeau

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@Noeloikeau

Hello,

Thank you for the wonderful library! I have a question regarding how to obtain the Riemannian Measure / Volume Element μ, also called the leading-left eigenvector of the transition probability matrix μP = μ.

In the original NLSA paper page 3, column 2, paragraph 2 and algorithm page 4, line 40, μ is given explicitly.

Am I correct in thinking that this quantity is calculated as the reciprocal of row_sum on line 136 of diffusion_map.py during the _left_normalize function, and subsequently discarded?

Thank you for any assistance.

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