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.
Full Documenation
- Instrument object providing an interface for downloading and analyzing a wide variety of science data sets.
- Uses pandas for the underlying data structure; capable of handling the many forms scientific measurements take in a consistent manner.
- 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.
- 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
- Instrument independent analysis routines.
- One simple way to get a complete science python package is from enthought
- at command line type
pip install pysat
- in python, run pysat.utils.set_data_dir('path to top level data dir')
- Nominal organization of data is top_dir/platform/name/tag/*/files
- netCDF support
- netCDF3 is supported by SciPy, no other libraries needed
- Download and install netCDF-4 C library
- Download and install python interface to netCDF using
pip install netCDF4 - CDF Support
- Download and install pysatCDF which supports a python CDF interface using
orpip install pysatCDFgit clone https://github.com/rstoneback/pysatCDF.git cd pysatCDF python setup.py build install