RESOURCECODE: A Python package for statistical analysis of sea-state hindcast data
Type | Article | ||||||||
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Date | 2023-03-23 | ||||||||
Language | English | ||||||||
Author(s) | Raillard Nicolas1, Chabot Simon2, Maisondieu Christophe1, Darbynian David3, Payne Gregory4, 5, Papillon Louis6 | ||||||||
Affiliation(s) | 1 : Ifremer, RDT, F-29280 Plouzané, France 2 : Logilab, Paris, France 3 : EMEC, Orkney, UK 4 : LHEEA, Ecole Centrale de Nantes and CNRS (UMR6598), 1 rue de la Noë, 44300 Nantes, France 5 : LHEEA, Ecole Centrale de Nantes and CNRS (UMR6598), 1 rue de la Noë, 44300 Nantes, France 6 : Innosea, Nantes, France |
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Source | Journal of Open Source Software (2475-9066) (Open Journals), 2023-03-23 , Vol. 8 , N. 83 , P. 4366 (4p.) | ||||||||
DOI | 10.21105/joss.04366 | ||||||||
Abstract | The resourcecode Marine Data Toolbox is a python package developed within the Resource- CODE project, to facilitate the access to a recently developed Metocean hindcast database (Accensi et al., 2021), and to a set of state-of-the-art methods for data analysis. This toolbox provides developers with a set of standard functions for resource assessment and operations planning. The advanced statistical modelling tools provided together with the embedded high resolution wave hindcast database provide the developers with a set of standard functions for resource assessment, extreme values modelling and operations and maintenance planning. Suitable for users not familiar with netCDF files handling or statistical analysis development, it is however designed to fulfil expert metocean analysis requirements. The advanced statistical modelling tools provided allow the developers of Offshore Renewable Energy (ORE) devices to conduct the necessary assessments to reduce uncertainty in expected environmental conditions, and de-risk investment in future technology design. |
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