{"id":26694471,"url":"https://github.com/deeplearnphysics/flow2supera","last_synced_at":"2025-04-13T00:35:14.624Z","repository":{"id":227362955,"uuid":"770625631","full_name":"DeepLearnPhysics/flow2supera","owner":"DeepLearnPhysics","description":null,"archived":false,"fork":false,"pushed_at":"2025-03-31T17:01:47.000Z","size":1594,"stargazers_count":0,"open_issues_count":2,"forks_count":4,"subscribers_count":5,"default_branch":"develop","last_synced_at":"2025-04-13T00:34:49.138Z","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DeepLearnPhysics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"contributing.md","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":"2024-03-11T21:44:50.000Z","updated_at":"2025-03-31T17:00:43.000Z","dependencies_parsed_at":"2024-03-12T23:33:43.448Z","dependency_job_id":"803b93e8-5763-4da2-9da0-0a0493d606ed","html_url":"https://github.com/DeepLearnPhysics/flow2supera","commit_stats":null,"previous_names":["deeplearnphysics/flow2supera"],"tags_count":17,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DeepLearnPhysics%2Fflow2supera","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DeepLearnPhysics%2Fflow2supera/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DeepLearnPhysics%2Fflow2supera/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DeepLearnPhysics%2Fflow2supera/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DeepLearnPhysics","download_url":"https://codeload.github.com/DeepLearnPhysics/flow2supera/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248650461,"owners_count":21139670,"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":[],"created_at":"2025-03-26T18:29:39.410Z","updated_at":"2025-04-13T00:35:14.591Z","avatar_url":"https://github.com/DeepLearnPhysics.png","language":"Python","readme":"# flow2supera\nThis repository contains code to translate the HDF5 files output by [ndlar_flow](https://github.com/DUNE/ndlar_flow) to [Supera](https://github.com/DeepLearnPhysics/SuperaAtomic) format for use by the DUNE machine learning reconstruction chain, [lartpc_mlreco3d](https://github.com/DeepLearnPhysics/lartpc_mlreco3d). \n\n# Prerequisites \n\n`flow2supera` depends on [edep2supera](https://github.com/DeepLearnPhysics/edep2supera), [SuperaAtomic](https://github.com/DeepLearnPhysics/SuperaAtomic), [larcv](https://github.com/DeepLearnPhysics/larcv2) and [h5flow](https://github.com/peter-madigan/h5flow). Install each of those repositories using the instructions on their respective READMEs and ensure that you can import them in python. Make sure the installation follows this order: `larcv` -\u003e `SuperaAtomic` -\u003e `edep2supera` -\u003e `flow2supera`.\n\n# Installation\nOnce the prerequisites are met, simply run this command from the top directory:\n```\npython3 -m pip install .\n```\n\n# Usage\n\nThe main executable script is located at `bin/run_flow2supera.py` relative to the top directory. The _required_ arguments are the input and output file names and the configuration:\n```\npython3 bin/run_flow2supera.py -o \u003coutput_file\u003e -c 2x2 \u003cinput_ndlar_flow_file\u003e\n```\nConfiguration keyword or a file path (full or relative including the file name). Supported configurations: `2x2`, `2x2_data`, `mod1_data`, `2x2_mpvmpr`.\nYou can also specify the following _optional_ arguments:\n- `-n` or `--num_events`: Number of events to process.\n- `-s` or `--skip`: Number of first events to skip.\n- `-l` or `--log`: Name of a log file to be created.\n\nUpon successful completion, this will produce an output larcv-format file that can be used as input to the machine learning reconstruction. \n\n# Contributing\n\nPlease read the contributing.md file for information on how you can contribute.\n\n# License\n\nDistributed under the MIT License. See LICENSE for more information.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeeplearnphysics%2Fflow2supera","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeeplearnphysics%2Fflow2supera","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeeplearnphysics%2Fflow2supera/lists"}