The Python Satellite Data Analysis Toolkit (pysat) is a package providing a simple and flexible interface for downloading, loading, cleaning, managing, processing, and analyzing scientific measurements. Though pysat was initially designed for in-situ satellite based measurements it aims to support all instruments in space science.
- Instrument object provides a single an interface for downloading and analyzing a wide variety of science data sets.
- Instrument independent analysis routines.
- Science data pipeline tasks of identifying files, loading, cleaning, and modifying data sets 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.
- Uses pandas for the underlying underlying data structure; capable of handling the many forms scientific measurements take in a consistent manner.
- 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/file breaks.
- Includes helper functions to reduce the barrier in adding new science instruments to pysat
Optional External Requirements
For data in CDF format:
- NASA CDF libraries
For data in netCDF format:
- netCDF3 files may be loaded using SciPy alone
- For netCDF4 files, Unidata netCDF libraries in C are required
TODO: Brief introduction on what you do with files - including link to relevant help section.