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 will be appearing the Sept/Oct 2018 issue of Computing in Science and Engineering!
If you are running version 0.3.3 from PyPi or have not recently updated your PySPLIT from GitHub and are performing moisture uptake analyses, please update to 0.3.4 and rerun your moisture uptake analyses immediately. Geographic points were previously assigned to
Trajectory.uptake backwards. This has been corrected.
- 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/
- Need help clustering?
- The class structure of PySPLIT has been rewritten:
Clusterobjects are now subclasses of
- Along-trajectory data for
HyPathclasses lives in the
dataattribute, a [GeoPandas] (http://geopandas.org/)
Clusterclasses are now subclasses of the
HyGroupclass. They are both iterable; they can also be added together or subtracted.
HyGroupare 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
Installing in a conda virtual environment:
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
$ conda create --name pysplitenv python=3.5 numpy matplotlib pandas basemap six fiona shapely geopandas
Similarly, for a Python 3.6 environment named
$ conda create --name pysplitenv python=3.6 numpy matplotlib pandas basemap six fiona shapely geopandas
Or, to create a Python 2.7 environment named
$ conda create --name pysplitenv python=2.7 numpy matplotlib pandas basemap six fiona=1.5.1 shapely geopandas
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.