A package for generating HYSPLIT air parcel trajectories trajectories, performing moisture uptake analyses, expediting HYSPLIT cluster analysis, and for visualizing trajectories, clusters, and along-trajectory meteorological data. For a basic overview of PySPLIT, see the SciPy 2015 conference proceedings.

A new, updated technical paper is coming soon in Computing in Science and Engineering! Current status: accepted!

• Python 3.6 support!
• HYSPLIT clustering fully in PySPLIT
• Increased trajectory generation functionality:
  • New modes
  • More control over trajectory initialization conditons
  • Improved meteorology discovery and better support for sub-weekly files
• Support for matrix and ensemble trajectories
• Extended library of examples
• Various quality of life/convenience updates and more!

• Support for Python 3.6
• PySPLIT now uses the power of GeoPandas rather than pure NumPy
• Faster trajectory file loading/Trajectory object initialization
• Need help clustering? pysplit.print_clusteringprocedure().
• The class structure of PySPLIT has been rewritten:
  • Trajectory and Cluster objects are now subclasses of HyPath class.
  • Along-trajectory data for HyPath classes lives in the data attribute, a [GeoPandas] (http://geopandas.org/) GeoDataFrame.
  • TrajectoryGroup and Cluster classes are now subclasses of the HyGroup class. They are both iterable; they can also be added together or subtracted.
  • HyPath and HyGroup are only used internally, so the API remains essentially the same.
• Trajectory generator updates:
  • Improved efficiency
  • Improved API
  • Use any weekly or semi-monthly meteorology data (see docs for required filename format), not just gdas1, and not just from the 21st century!
  • Generate trajectories for every day in each month OR for particular slice of days in each month
  • Generate reverse trajectories at time of bulk trajectory generation OR during your analysis workflow!
• Choose the starting point for your moisture uptake analyses
• Removal of certain assumptions about trajectory file structure for HYSPLIT January 2017 (854) compatibility.
• Removal of certain assumptions about trajectory century and timepoint interval from loading process
• Check out the growing library of examples!

PySPLIT is compatible with Python 2.7, 3.5, and 3.6. It depends on:

• NumPy >= 1.6
• matplotlib >= 1.2
• Basemap >= 1.0
• GeoPandas >= 0.1

and is available on PyPi. You can install the latest stable release by running:

$ pip install pysplit

To install from source or create a development installation, clone and fork PySPLIT then install by running:

$ python setup.py install

or develop locally by running:

$ python setup.py develop

Installation 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:

$ conda config --add channels conda-forge

Next, create the conda environment. For a Python 3.5 environment named pysplitenv, run:

$ conda create --name pysplitenv python=3.5 numpy matplotlib pandas basemap six fiona shapely geopandas

Similarly, for a Python 3.6 environment named pysplitenv, run:

$ conda create --name pysplitenv python=3.6 numpy matplotlib pandas basemap six fiona shapely geopandas

Or, to create a Python 2.7 environment named pysplitenv, run:

$ conda create --name pysplitenv python=2.7 numpy matplotlib pandas basemap six fiona=1.5.1 shapely geopandas

Activate pysplitenv by running the following on Windows:

$ activate pysplitenv

If you are on Linux or OSX, instead run:

$ source activate pysplitenv

Within your virtual environment, install PySPLIT as above.

Updated examples can be found in docs/examples, and an updated technical paper is pending. For now, if you use PySPLIT in your work, please cite the SciPy 2015 conference proceedings. Many thanks are due to the NOAA Air Research Laboratory for providing the HYSPLIT model.