{"id":19855807,"url":"https://github.com/ray-chew/probabilistic_forecasting_examples","last_synced_at":"2026-06-09T02:01:53.070Z","repository":{"id":228576297,"uuid":"774368453","full_name":"ray-chew/probabilistic_forecasting_examples","owner":"ray-chew","description":"Reproduced the examples and results from the textbook \"Probabilistic Forecasting and Bayesian Data Assimilation\"  in Python","archived":false,"fork":false,"pushed_at":"2024-03-23T23:45:43.000Z","size":9853,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-11T13:54:41.688Z","etag":null,"topics":["bayesian-optimization","data-assimilation","probabilistic-forecasting","textbook-example"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ray-chew.png","metadata":{"files":{"readme":"README.md","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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-03-19T12:34:51.000Z","updated_at":"2024-06-21T18:41:47.000Z","dependencies_parsed_at":"2025-01-11T13:48:17.748Z","dependency_job_id":"6c22ac41-4890-4e33-bdc6-2ed1573ed93d","html_url":"https://github.com/ray-chew/probabilistic_forecasting_examples","commit_stats":null,"previous_names":["ray-chew/probabilistic_forecasting_examples"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Fprobabilistic_forecasting_examples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Fprobabilistic_forecasting_examples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Fprobabilistic_forecasting_examples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ray-chew%2Fprobabilistic_forecasting_examples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ray-chew","download_url":"https://codeload.github.com/ray-chew/probabilistic_forecasting_examples/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241245642,"owners_count":19933296,"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":["bayesian-optimization","data-assimilation","probabilistic-forecasting","textbook-example"],"created_at":"2024-11-12T14:13:45.671Z","updated_at":"2026-06-09T02:01:48.049Z","avatar_url":"https://github.com/ray-chew.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Examples in Python from the textbook [*Probabilistic Forecasting and Bayesian Data Assimilation*](https://www.math.uni-potsdam.de/~sreich/probabilisticForecastingAndBayesianDataassimilation.html)\n\nIn November 2018, I read this textbook from cover to cover and reproduced the examples to gain an understanding of data assimilation.\n\n---\n\n### Todo:\n1. Check mean values for chap5ex17.\n2. Complete Chapter 7 example 13\n    1. Implement ESRF filter\n    2. Fix the implementation of the SIR\n    3. Fix ETPF 3d residual calculations\n    4. Use a FORTRAN subroutine for the implicit solver\n3. Check what is wrong with chapter 8 example 5.\n4. Chapter 8 example 9: The matrix PP is introduced to make sure that the mean of the generated ensemble spread does not change (sum over all the ensemble members at a given spatial grid point equals zero). Is this true? Think about it.\n5. Might want to implement chap8ex13 and chap8ex21 as a challenge.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Fprobabilistic_forecasting_examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fray-chew%2Fprobabilistic_forecasting_examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fray-chew%2Fprobabilistic_forecasting_examples/lists"}