Code for stochastic area metric: binary search for speed

M. de Angelis; J. Sunny

doi:10.5281/ZENODO.6366288

Code for stochastic area metric: binary search for speed

M. de Angelis, J. Sunny

Civil And Environmental Engineering

Research output: Non-textual form › Software

Abstract

This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.

Original language	English
DOIs	https://doi.org/10.5281/ZENODO.6366288
Publication status	Published - 17 Mar 2022

Keywords

Wasserstein distances
area metric
binary search

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10.5281/ZENODO.6366288

1 Article

Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties
Sunny, J., de Angelis, M. & Edwards, B., 1 Apr 2024, In: Journal of Seismology. 28, 2, p. 303-320 18 p.
Research output: Contribution to journal › Article › peer-review

Open Access
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1 Citation (Scopus)

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Cite this

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title = "Code for stochastic area metric: binary search for speed",

abstract = "This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.",

keywords = "Wasserstein distances, area metric, binary search",

author = "{de Angelis}, M. and J. Sunny",

year = "2022",

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language = "English",

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AU - Sunny, J.

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N2 - This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.

AB - This repository contains Python scientific code for computing efficiently the area metric, a.k.a. 1-Wasserstein distance, between tabular samples. The code is optimized by running Numpy under the hood, thus is as vectorized as possible. A basic Matlab version is also present in this repository.

KW - Wasserstein distances

KW - area metric

KW - binary search

U2 - 10.5281/ZENODO.6366288

DO - 10.5281/ZENODO.6366288

M3 - Software

ER -

Code for stochastic area metric: binary search for speed

Abstract

Keywords

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Research output

Regionally adjusted stochastic earthquake ground motion models, associated variabilities and epistemic uncertainties

Cite this