pysat 0.2.2

Supports science data analysis across measurement platforms

The Python Science 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.

Main Features

• Single interface for a wide variety of science data sets.

• Single interface to download data for all supported instruments.

• Data model (modified pandas) that supports a combination of 1D, 2D, 3D, and nD data in a single structure

• Instrument independent analysis routines.

• Science data pipeline tasks of identifying files, loading, and cleaning data sets are built into the instrument object.

• Supports the automatic application of arbitray custom functions upon each load. This nano-kernel functionality ensures that any routine that interacts with the instrument object receives properly processed data.

• 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

• Iterates by day/file using the for loop, manual next/prev methods, or any iterative method.

• Iterate through a data set orbit-by-orbit; orbits are calculated on the fly from loaded data and span day/month/year breaks.

• Iterate over custom seasons

• Supports rigorous time-series calculations. Appends a data buffer to provide spin up/down time for time series methods to produce an accurate analysis. Buffer automatically added/removed.

• Uses pandas for the underlying underlying data structure; capable of handling the many forms scientific measurements take in a consistent manner.

• pandas has been forked to accomodate the assignment of pandas Series/Dataframes as single elements of a Series/Dataframe.

• Includes helper functions to reduce the barrier to adding new science instruments to pysat

Documentation

Full Documentation

External Requirements

For data in CDF format:

• NASA CDF libraries

• spacepy

For data in netCDF format:

• Unidata netCDF libraries in C

• netCDF4