{"id":22894193,"url":"https://github.com/sentient-codebot/tsfm-rlp-forecast","last_synced_at":"2026-02-11T14:03:27.312Z","repository":{"id":263577547,"uuid":"822607293","full_name":"sentient-codebot/TSFM-RLP-Forecast","owner":"sentient-codebot","description":null,"archived":false,"fork":false,"pushed_at":"2024-11-25T19:53:57.000Z","size":1108,"stargazers_count":2,"open_issues_count":1,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-09-08T21:55:49.502Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sentient-codebot.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"zenodo":null}},"created_at":"2024-07-01T13:17:39.000Z","updated_at":"2024-11-12T11:33:01.000Z","dependencies_parsed_at":"2024-11-19T10:22:45.461Z","dependency_job_id":"892fcd87-662d-4da3-93bf-e82cb7e509fd","html_url":"https://github.com/sentient-codebot/TSFM-RLP-Forecast","commit_stats":null,"previous_names":["sentient-codebot/tsfm-rlp-forecast"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sentient-codebot/TSFM-RLP-Forecast","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sentient-codebot%2FTSFM-RLP-Forecast","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sentient-codebot%2FTSFM-RLP-Forecast/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sentient-codebot%2FTSFM-RLP-Forecast/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sentient-codebot%2FTSFM-RLP-Forecast/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sentient-codebot","download_url":"https://codeload.github.com/sentient-codebot/TSFM-RLP-Forecast/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sentient-codebot%2FTSFM-RLP-Forecast/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29333921,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-11T12:42:24.625Z","status":"ssl_error","status_checked_at":"2026-02-11T12:41:23.344Z","response_time":97,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":[],"created_at":"2024-12-13T23:17:08.325Z","updated_at":"2026-02-11T14:03:27.283Z","avatar_url":"https://github.com/sentient-codebot.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Time Series Foundation Models for Residential Load Profile Forecasting\n\nThis project aims to compare the zero-shot forecast performance of Time Series Foundation Models (TSFMs) on various scales of residential load profile (RLP) forecasting problems. \n\nThis is the official repository of paper: [Link to paper](). \n\n## Logging Result Procedure\n\nExample: *exp/chronos/chronos_predictor.py*\n\n1. import `utility.configuration` (as `cf`) and `exp.eva_metrics` (as `evm`) modules.\n2. generate a unique `exp_id` for each run. `exp_id=cf.generate_time_id()`\n3. for each sub-run (e.g. with different country, resolution.)\n   1. log data configuration `data_config=cf.DataConfig(country='nl',...)`\n   2. log model configuration `model_config=cf.ModelConfig(model='chronos',...)`\n   3. log evaluation results `eval_metrics=evm.EvaluationMetrics(...)`\n   4. integrate into `exp_config=cf.ExperimentConfig(exp_id=exp_id, data=data_config, model=model_config, eval_metrics=eval_metrics)`\n   5. save to .csv `exp_config.append_csv(f'result/{exp_id}.csv')`\n\n## Structure\n\n### File Structure\n\n- dataset: contains class definition of datasets used in the project. \n  - XXX.py: class definition of dataset XXX.\n  - ...: data preprocessing. \n- model: contains the (wrapper) class of the TSFMs used in the project.\n  - YYY.py: class definition of TSFM YYY.\n- utility: contains utility functions used in the project, including data \n  - argument_parser.py: argument parser for the project.\n  - configuration.py: configuration class definition. \n- configs: .yaml configuration files. \n\n### Configuration Usage\n\nThe configuration module defines a basic configuration class that can be extended to contain configuration settings for data, model, etc. The base class allows for easy conversion between dictionary, configuration object, and .yaml file. \n\n#### Configuration Hierachy\n\n- ExperimentConfig\n  - general experiment-specific settings such as `exp_id`.\n  - data: DataConfig. configuration for data.\n  - model: ModelConfig. configuration for model.\n  - ...","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsentient-codebot%2Ftsfm-rlp-forecast","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsentient-codebot%2Ftsfm-rlp-forecast","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsentient-codebot%2Ftsfm-rlp-forecast/lists"}