{"id":17319902,"url":"https://github.com/saransh-cpp/pyhep22-constructing-hep-vectors-and-analyzing-hep-data-using-vector","last_synced_at":"2025-04-14T15:30:44.482Z","repository":{"id":105022281,"uuid":"533695568","full_name":"Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector","owner":"Saransh-cpp","description":"PyHEP 2022 notebook talk - Constructing HEP vectors and analyzing HEP data using Vector","archived":false,"fork":false,"pushed_at":"2025-02-21T00:45:47.000Z","size":3590,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-28T04:24:04.400Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://indico.cern.ch/event/1150631/contributions/5014393/","language":"Jupyter Notebook","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/Saransh-cpp.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":"2022-09-07T09:26:48.000Z","updated_at":"2025-02-21T00:45:50.000Z","dependencies_parsed_at":null,"dependency_job_id":"65e35622-fa72-4d02-bb4c-722ae20aa423","html_url":"https://github.com/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector","commit_stats":{"total_commits":47,"total_committers":3,"mean_commits":"15.666666666666666","dds":0.4893617021276596,"last_synced_commit":"ba771131917534ef74acec375149eba13b7a9eef"},"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Saransh-cpp%2FPyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Saransh-cpp%2FPyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Saransh-cpp%2FPyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Saransh-cpp%2FPyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Saransh-cpp","download_url":"https://codeload.github.com/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248906348,"owners_count":21181160,"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":"2024-10-15T13:28:02.363Z","updated_at":"2025-04-14T15:30:44.475Z","avatar_url":"https://github.com/Saransh-cpp.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# PyHEP 2022 Notebook talk - Constructing HEP vectors and analyzing HEP data using Vector\n\n[![Talk](https://img.shields.io/badge/PyHEP22-notebook_talk-blue?logo=github\u0026logoColor=white\u0026color=blue)](https://indico.cern.ch/event/1150631/contributions/5014393/)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/HEAD?urlpath=lab/tree/talk.ipynb)\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/blob/main/talk.ipynb)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7081003.svg)](https://doi.org/10.5281/zenodo.7081003)\n\n[Vector](https://iris-hep.org/projects/vector.html) is a Python library for 2D, 3D, and Lorentz vectors, including arrays of vectors, designed to solve common physics problems in a NumPy-like way. Vector currently supports pure Python Object, NumPy, Awkward, and Numba-based (Numba-Object, Numba-Awkward) backends.\n\nThis talk will focus on introducing Vector and its backends to the HEP community through a data analysis pipeline. The session will build up from pure Python Object based vectors to Awkward based vectors, ending with a demonstration of Numba support. Furthermore, we will discuss the latest developments in the library's API and showcase some recent enhancements.\n\n## Setup\n\nThere are two ways to follow along (or run this notebook after the talk) -\n\n1. Locally\n\n    - Clone [this](https://github.com/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector.git) repository -\n    ```bash\n    git clone https://github.com/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector.git\n    ```\n\n    - Change directory\n    ```bash\n    cd Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector\n    ```\n\n    - Launch the classic Jupyter notebook or Jupyter lab -\n    ```bash\n    jupyter notebook\n    # or\n    jupyter lab\n    ```\n\n2. On cloud (recommended)\n\n    - Binder (recommended)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/HEAD?urlpath=lab/tree/talk.ipynb)\n\n    - Google Colab\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Saransh-cpp/PyHEP22-Constructing-HEP-vectors-and-analyzing-HEP-data-using-Vector/blob/main/talk.ipynb)\n\nWe will be directly importing `vector`, `awkward`, `numpy`, `numba`, `uproot`, `matplotlibn`, and `scikit-hep-testdata` in this tutorial. Hence, a user must install these packages if this notebook is being run locally or on Google Colab.\n\n## Recent developments\n\nVector [`v0.9.0`](https://github.com/scikit-hep/vector/releases/tag/v0.9.0) is out!\n- Features: improved reprs, deltaRapidityPhi, backends are public now, …\n- Documentation: major documentation overhaul, doctests, CITATION.cff, …\n- Bug fixes: type checks, fix nan_to_num, …\n- Maintenance: hatchling backend, support awkward._v2 in tests, build and test on Python 3.10 and 3.11-dev, …\n\nMore about `v0.9.0` here - https://vector.readthedocs.io/en/latest/changelog.html#version-0-9\n\n---\n\nVector [`v0.10.0`](https://github.com/scikit-hep/vector/releases/tag/v0.10.0) is out too!\n- Removed support for Python 3.6\n\nMore about `v0.10.0` here - https://vector.readthedocs.io/en/latest/changelog.html#version-0-10\n\n## Near future development plans\n\n- Better constructors (under work)\n- A benchmarking suite\n- Benchmarks against Root\n- A complete `awkward` `v2` support (scheduled for December)\n- NumPy-Numba backend\n- Other potential backends -\n\nVector was scheduled to have a major release (`v1.0.0`) before `PyHEP 2022`, but that was unfortunately delayed. A major release can be expected in October, which would primarily be introducing new constructors.\n\nOpen for user feedback and discussions!\n\n## Stuck somewhere? Reach out!\n\n- If something is not working the way it should, or if you want to request a new feature, create a [new issue](https://github.com/scikit-hep/vector/issues) on GitHub.\n- To discuss something related to vector, use the [discussions](https://github.com/scikit-hep/vector/discussions/) tab on GitHub or vector’s gitter ([Scikit-HEP/vector](https://gitter.im/Scikit-HEP/vector)) chat room.\n- Have a look at vector's [releases](https://github.com/scikit-hep/vector/releases) to stay up-to-date!\n\n## Cite vector\n\nIf you use `vector` in your work, please cite it using the following metadata -\n\n```bib\n@software{Schreiner_vector,\nauthor = {Schreiner, Henry and Pivarski, Jim and Chopra, Saransh},\ndoi = {10.5281/zenodo.5942082},\nlicense = {BSD-3-Clause},\ntitle = {{vector}},\nurl = {https://github.com/scikit-hep/vector}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaransh-cpp%2Fpyhep22-constructing-hep-vectors-and-analyzing-hep-data-using-vector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaransh-cpp%2Fpyhep22-constructing-hep-vectors-and-analyzing-hep-data-using-vector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaransh-cpp%2Fpyhep22-constructing-hep-vectors-and-analyzing-hep-data-using-vector/lists"}