pysat 3.2.1

Supports science analysis across disparate data platforms

pysat: Python Satellite Data Analysis Toolkit

The Python Satellite Data Analysis Toolkit (pysat) provides a simple and flexible interface for robust data analysis from beginning to end - including downloading, loading, cleaning, managing, processing, and analyzing data. Pysat's plug-in design allows analysis support for any data, including user provided data sets. The pysat team provides a variety of plug-ins to support public scientific data sets in packages such as pysatNASA, pysatMadrigal, and more, available as part of the general pysat ecosystem.

Full Documentation

JGR-Space Physics Publication

Pysat Ecosystem Publication

Citation Info

Come join us on Slack! An invitation to the pysat workspace is available in the 'About' section of the pysat GitHub Repository. Development meetings are generally held fortnightly.

Main Features

• Instrument independent analysis routines.
• Instrument object providing an interface for downloading and analyzing a wide variety of science data sets.
  • Uses pandas or xarray for the underlying data structure; capable of handling the many forms scientific measurements take in a consistent manner.
  • Standard scientific data handling tasks (e.g., identifying, downloading, and loading files and cleaning and modifying data) are built into the Instrument object.
  • Supports metadata consistent with the netCDF CF-1.6 standard. Each variable has a name, long name, and units. Note units are informational only.
• Simplifies data management
  • Iterator support for loading data by day/file/orbit, independent of data storage details.
  • Orbits are calculated on the fly from loaded data and span day breaks.
  • Iterate over custom seasons
• Supports rigorous time-series calculations that require spin up/down time across day, orbit, and file breaks.
• Includes helper functions to reduce the barrier in adding new science instruments to pysat

Installation

The following instructions provide a guide for installing pysat and give some examples on how to use the routines.

Prerequisites

pysat uses common Python modules, as well as modules developed by and for the Space Physics community. This module officially supports Python 3.X+.

Common modules	Community modules
dask	netCDF4
numpy >= 1.12
pandas
portalocker
pytest
scipy
toolz
xarray

PyPi Installation

pip install pysat

Note that while support for python 3.6 is maintained for opertional purposes, there have been issues with installing through PyPi on older systems. Installation through GitHub is recommended for older systems.

GitHub Installation

git clone https://github.com/pysat/pysat.git

Change directories into the repository folder and run the pyproject.toml or setup.py file. For a local install use the "--user" flag after "install".

cd pysat/
python -m build .
pip install .

Using pysat

• The first time pysat is run, you will need to specify a directory to store the data. In Python, run:

pysat.params['data_dirs'] = 'path/to/directory/that/may/or/may/not/exist'

• Nominal organization of data is top_dir/platform/name/tag/inst_id/files

Detailed examples and tutorials for using pysat are available in the documentation.