{"id":13686418,"url":"https://github.com/mscross/pysplit","last_synced_at":"2026-01-16T13:55:24.446Z","repository":{"id":34635902,"uuid":"38587932","full_name":"mscross/pysplit","owner":"mscross","description":"A package for HYSPLIT air parcel trajectory analysis.","archived":false,"fork":false,"pushed_at":"2024-01-09T20:54:17.000Z","size":382,"stargazers_count":162,"open_issues_count":39,"forks_count":83,"subscribers_count":17,"default_branch":"master","last_synced_at":"2025-05-01T09:38:55.721Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mscross.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}},"created_at":"2015-07-05T23:24:57.000Z","updated_at":"2025-04-15T15:19:32.000Z","dependencies_parsed_at":"2024-03-02T23:44:17.493Z","dependency_job_id":null,"html_url":"https://github.com/mscross/pysplit","commit_stats":{"total_commits":200,"total_committers":8,"mean_commits":25.0,"dds":"0.29500000000000004","last_synced_commit":"f63ad3e22dada5a97d05ac5d8aa85040d016cd28"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/mscross/pysplit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mscross%2Fpysplit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mscross%2Fpysplit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mscross%2Fpysplit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mscross%2Fpysplit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mscross","download_url":"https://codeload.github.com/mscross/pysplit/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mscross%2Fpysplit/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28479034,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-16T11:59:17.896Z","status":"ssl_error","status_checked_at":"2026-01-16T11:55:55.838Z","response_time":107,"last_error":"SSL_read: 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":"2024-08-02T15:00:32.064Z","updated_at":"2026-01-16T13:55:24.431Z","avatar_url":"https://github.com/mscross.png","language":"Python","readme":"# PySPLIT\n\nA package for generating [HYSPLIT](http://ready.arl.noaa.gov/HYSPLIT.php) air parcel trajectories trajectories, performing moisture uptake analyses, expediting HYSPLIT cluster analysis, and for visualizing trajectories, clusters, and along-trajectory meteorological data.\n\nFor an overview and brief history of PySPLIT, a new, updated technical paper- Introduction to PySPLIT: A Python Toolkit for NOAA ARL’s HYSPLIT Model- can be found in the Sept/Oct 2018 (vol 20, issue 5, p. 47-62 ) issue of *Computing in Science and Engineering*!  This supercedes the [SciPy 2015 conference proceedings](http://conference.scipy.org/proceedings/scipy2015/mellissa_cross_p.html).\n\n### If you are running version 0.3.3 or older and are performing moisture uptake analyses, please update PySPLIT and rerun your moisture uptake analyses immediately.  Geographic points were previously assigned to ``Trajectory.uptake`` backwards.  This has been corrected.\n\n## Coming Soon\n* HYSPLIT clustering fully in PySPLIT\n* Increased trajectory generation functionality:\n  * New modes\n  * More control over trajectory initialization conditons\n  * Improved meteorology discovery and better support for sub-weekly files\n* Support for matrix and ensemble trajectories\n* Extended library of examples\n* Various quality of life/convenience updates and more!\n\n\n## Past Updates\n\n* Support for Cartopy (basemap use to be deprecated in future update)\n* Support for Python 3.6 and 3.7\n* PySPLIT now uses the power of GeoPandas rather than pure NumPy\n* Faster trajectory file loading/``Trajectory`` object initialization\n* Need help clustering?  ``pysplit.print_clusteringprocedure()``.\n* The class structure of PySPLIT has been rewritten:\n  * ``Trajectory`` and ``Cluster`` objects are now subclasses of ``HyPath`` class.\n  * Along-trajectory data for ``HyPath`` classes lives in the ``data`` attribute, a [GeoPandas] (http://geopandas.org/) ``GeoDataFrame``.\n  * ``TrajectoryGroup`` and ``Cluster`` classes are now subclasses of the ``HyGroup`` class.  They are both iterable; they can also be added together or subtracted.\n  * ``HyPath`` and ``HyGroup`` are only used internally, so the API remains essentially the same.\n* Trajectory generator updates:\n  * Improved efficiency\n  * Improved API\n  * Use *any* weekly or semi-monthly meteorology data (see docs for required filename format), not just gdas1, and not just from the 21st century!\n  * Generate trajectories for every day in each month *OR* for particular slice of days in each month\n  * Generate reverse trajectories at time of bulk trajectory generation OR during your analysis workflow!\n* Choose the starting point for your moisture uptake analyses\n* Removal of certain assumptions about trajectory file structure for HYSPLIT January 2017 (854) compatibility.\n* Removal of certain assumptions about trajectory century and timepoint interval from loading process\n* Check out the growing library of examples!\n## Installing PySPLIT\n\nPySPLIT is compatible with Python 2.7, 3.6, and 3.7.  It depends on:\n* NumPy \u003e= 1.6\n* matplotlib \u003e= 1.2\n* Basemap \u003e= 1.0\n* GeoPandas \u003e= 0.1\n* Cartopy \u003e= 0.15\n\nand is available on PyPi.  You can install the latest stable release by running:\n\n```\n$ pip install pysplit\n```\n\nTo install from source or create a development installation, clone and fork PySPLIT then install by running:\n\n```\n$ python setup.py install\n```\n\nor develop locally by running:\n\n```\n$ python setup.py develop\n```\n\n### Installing in a conda virtual environment:\n\nInstallation difficulties with PySPLIT are typically related to GeoPandas dependencies.  An easy work-around is installing PySPLIT in a new conda virtual environment.  This is the recommended installation method.  First, add the conda-forge channel:\n```\n$ conda config --add channels conda-forge\n```\n\nNext, create the conda environment.  For a Python 3.6 environment named `pysplitenv`, run:\n```\n$ conda create --name pysplitenv python=3.6 numpy matplotlib pandas basemap six fiona shapely geopandas cartopy\n```\n\nSimilarly, for a Python 3.7 environment named `pysplitenv`, run:\n```\n$ conda create --name pysplitenv python=3.7 numpy matplotlib pandas basemap six fiona shapely geopandas cartopy\n```\n\nOr, to create a Python 2.7 environment named `pysplitenv`, run:\n```\n$ conda create --name pysplitenv python=2.7 numpy matplotlib pandas basemap six fiona=1.5.1 shapely geopandas cartopy\n```\n\nActivate `pysplitenv` by running the following on Windows:\n```\n$ activate pysplitenv\n```\nIf you are on Linux or OSX, instead run:\n```\n$ source activate pysplitenv\n```\n\nWithin your virtual environment, install PySPLIT as above.\n\n## Using PySPLIT\n\nExamples can be found in docs/examples.  PySPLIT is currently tested on Windows 7 using HYSPLIT revision 927 (Feb. 2018) and the preferred PySPLIT installation methods listed above.   Many thanks are due to the NOAA Air Research Laboratory for providing the HYSPLIT model.\n","funding_links":[],"categories":["Numerical Model"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmscross%2Fpysplit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmscross%2Fpysplit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmscross%2Fpysplit/lists"}