{"id":15555245,"url":"https://github.com/brews/baysplinepy","last_synced_at":"2025-04-23T19:49:08.136Z","repository":{"id":57414235,"uuid":"115745915","full_name":"brews/baysplinepy","owner":"brews","description":"The BAYSPLINE alkenone UK'37 calibration, in Python.","archived":false,"fork":false,"pushed_at":"2020-02-04T17:06:51.000Z","size":202,"stargazers_count":4,"open_issues_count":2,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-17T01:27:36.066Z","etag":null,"topics":["alkenone","bayesian-inference","calibration","marine","paleoceanography","paleoclimate","python","uk37"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/brews.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-12-29T18:42:22.000Z","updated_at":"2023-10-19T08:17:11.000Z","dependencies_parsed_at":"2022-08-26T20:45:31.112Z","dependency_job_id":null,"html_url":"https://github.com/brews/baysplinepy","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brews%2Fbaysplinepy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brews%2Fbaysplinepy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brews%2Fbaysplinepy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brews%2Fbaysplinepy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/brews","download_url":"https://codeload.github.com/brews/baysplinepy/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250504085,"owners_count":21441527,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["alkenone","bayesian-inference","calibration","marine","paleoceanography","paleoclimate","python","uk37"],"created_at":"2024-10-02T15:07:31.621Z","updated_at":"2025-04-23T19:49:08.119Z","avatar_url":"https://github.com/brews.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"baysplinepy\n===========\n\n.. image:: https://travis-ci.org/brews/baysplinepy.svg?branch=master\n    :target: https://travis-ci.org/brews/baysplinepy\n\n\nAn open source Python package for `alkenone UK'37 \u003chttps://en.wikipedia.org/wiki/Alkenone\u003e`_ calibration.\n\n**baysplinepy** is based on the original BAYSPLINE software for MATLAB (https://github.com/jesstierney/BAYSPLINE). BAYSPLINE is a Bayesian calibration for the alkenone paleothermometer, as published in `Tierney \u0026 Tingley (2018) \u003chttp://doi.org/10.1002/2017PA003201\u003e`_. \n\nNOTE that this package is under active development. Code and documentation may not be complete and may change in the near future.\n\n\nExample\n-------\n\nFirst, load packages and an example dataset::\n\n    import numpy as np\n    import bayspline as bsl\n\n    example_file = bsl.get_example_data('tierney2016-p178-15p.csv')\n    d = np.genfromtxt(example_file, delimiter=',', names=True)\n\nThis dataset (from `Tierney et al. 2015 \u003chttps://doi.org/10.1038/ngeo2603\u003e`_)\nhas three columns giving core depth (cm), sediment age (calendar years BP), and UK'37.\n\nWe can predict sea-surface temperatures (SST) from UK'37 with ``bsl.predict_sst()``::\n\n    prediction = bsl.predict_sst(d['uk37'], prior_std=10)\n\nTo see actual numbers from the prediction, directly parse ``prediction.ensemble`` or use ``prediction.percentile()`` to get the 5%, 50% and 95% percentiles.\n\nYou can also plot your prediction with ``bsl.predictplot()`` or ``bsl.densityplot()``.\n\nAlternatively, we can make inferences about UK'37 from SST with ``bsl.predict_uk()``::\n\n    sst = np.arange(1, 25)\n    prediction = bsl.predict_uk(sst)\n\n\nInstallation\n------------\n\nInstall **baysplinepy** in ``conda`` with::\n\n    $ conda install baysplinepy -c sbmalev\n\nTo install with ``pip``, run::\n\n    $ pip install baysplinepy\n\nUnfortunately, **baysplinepy** is not compatible with Python 2.\n\n\nSupport and development\n-----------------------\n\n- Please feel free to report bugs and issues or view the source code on GitHub (https://github.com/brews/baysplinepy).\n\n\nLicense\n-------\n\n**baysplinepy** is available under the Open Source GPLv3 (https://www.gnu.org/licenses).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrews%2Fbaysplinepy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrews%2Fbaysplinepy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrews%2Fbaysplinepy/lists"}