{"id":20200814,"url":"https://github.com/openclimatefix/ocf-ml-metrics","last_synced_at":"2025-04-10T11:21:23.737Z","repository":{"id":99304335,"uuid":"588129989","full_name":"openclimatefix/ocf-ml-metrics","owner":"openclimatefix","description":"Collection of simple baseline models and metrics for standardized evaluation of OCF forecasting models","archived":false,"fork":false,"pushed_at":"2025-04-07T17:30:29.000Z","size":55,"stargazers_count":4,"open_issues_count":5,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-07T18:37:57.906Z","etag":null,"topics":["metrics"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/openclimatefix.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},"funding":{"github":["openclimatefix"],"patreon":null,"open_collective":"openclimatefix","ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"custom":null}},"created_at":"2023-01-12T11:56:05.000Z","updated_at":"2023-07-24T10:00:33.000Z","dependencies_parsed_at":"2023-05-23T12:00:41.966Z","dependency_job_id":"76300c30-5eca-47cd-96f5-b826dac82865","html_url":"https://github.com/openclimatefix/ocf-ml-metrics","commit_stats":{"total_commits":58,"total_committers":5,"mean_commits":11.6,"dds":0.3793103448275862,"last_synced_commit":"0e49db7ebd96a99916fa90a2df3cc947e28c628e"},"previous_names":[],"tags_count":10,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openclimatefix%2Focf-ml-metrics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openclimatefix%2Focf-ml-metrics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openclimatefix%2Focf-ml-metrics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/openclimatefix%2Focf-ml-metrics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/openclimatefix","download_url":"https://codeload.github.com/openclimatefix/ocf-ml-metrics/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248208603,"owners_count":21065203,"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":["metrics"],"created_at":"2024-11-14T04:45:45.158Z","updated_at":"2025-04-10T11:21:23.704Z","avatar_url":"https://github.com/openclimatefix.png","language":"Python","funding_links":["https://github.com/sponsors/openclimatefix","https://opencollective.com/openclimatefix"],"categories":[],"sub_categories":[],"readme":"# ocf-ml-metrics\nCollection of simple baseline models and metrics for standardized evaluation of OCF forecasting models.\n\nThis package computes a variety of baselines and error metrics\nincluding persistence of both last value and last day of generation,\ncomparison to PVLive, and max and zero baselines.\n\n## Installation\n\nInstall with `pip install ocf-ml-metrics`\n\n## Usage\n\nThe easiest way to use this package is to use the\nconvenience function `ocf_ml_metrics.metrics.errors.compute_metrics` that\ncomputes all the basic error metrics overall, with and without night time,\nfor different parts of the year, different times of day, and all forecast\nhorizons by default.\n\nThere is also `ocf_ml_metrics.evaluation.evaluation.evaluation` that computes metrics after taking in a pandas\ndataframe. These metrics are computed for the raw values, normalized values, against simple baseline models,\nand per ID in the input dataframe. The input dataframe required data can be found in the docstring\n\nAnd example usage would be\n\n```python\nfrom ocf_ml_metrics.evaluation.evaluation import evaluation\nimport pandas as pd\n\nresults_df = pd.read_csv('\u003cpath to csv\u003e')\n\nmetrics: dict = evaluation(results_df=results_df, model_name='\u003cmodel name\u003e')\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenclimatefix%2Focf-ml-metrics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenclimatefix%2Focf-ml-metrics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenclimatefix%2Focf-ml-metrics/lists"}