das2py - space physics data client

Find a server and load data in three lines of code

import das2

src = das2.get_source( 'site:/uiowa/galileo/pws/survey_electric/das2' )
dataset = src.get( {'time' : ('1997-05-07T15:00', '1997-05-07T17:00', 4.0)} )[0]

Servers come and go, the federated catalog maps IDs to data sources.
Browse for UIDs using a das2 catalog browser or search using VESPA.

Access quantities by physical dimensions

print(dataset)

vX = dataset['time']['center']
vY = dataset['frequency']['center']
vZ = dataset['electric']['center']

Datasets contain dimensions. Dimensions contain variables. Each variable in a dimension serves a purpose, the most common is to define the center point of a coordinate or measurement.
Array dimensions are not confused with physical dimensions. Dataset meaning is not tied to any particular array morphology.

Plot using the graphics package you already know

import matplotlib.pyplot as pyplot
import matplotlib.colors as colors

fig, ax = pyplot.subplots()
scaleZ = colors.LogNorm(vmin=vZ.array.min(), vmax=vZ.array.max())
ax.pcolormesh(vX.array, vY.array, vZ.array, norm=scaleZ, cmap='jet')
pyplot.show()

Code for plotting data from Cassini, Juno, Mars Express, Voyager and other spacecraft may be found in the das2py examples directory.
Examples are also available for general tasks such as catalog navigation, data source interface discovery, manual dataset creation and writing ephemeris annotations on X-axis tics.

Installation

The preferred installation method uses Anaconda since das2py relies on native C code for efficent delivery of data to numpy arrays.

conda install matplotlib
conda install -c dasdevelopers das2py

At present the packages are hosted by the DasDevelopers Anaconda cloud organization. We may move to submitting conda-forge packages in the future.

Instructions for building and testing das2py from source code may be found in the README.md file included in with the sources. To get the source run:

git clone git@github.com:das-developers/das2C.git
git clone git@github.com:das-developers/das2py.git

or use the git clone method you prefer to download both das2py and das2C.

Documentation

The das2py 2019 AGU poster provides a quick overview of server and data organization in das2py as well as sample code.

das2py sphinx documents provide an overview of das2.3 and serve as a reference for the functions in the pure python das2 module as well as the _das2 C extension.

Related Software

das2py-server is a CGI program that receives requests for data and runs the appropriate server side commands to generate the desired output stream at the desired time resolution. It's a caching middleware layer between full-resolution data readers and remote clients.

das2C is the portable C library that underpins das2py, das2D, das2dlm and provides stream efficent stream processing tools. The source code is available under the LGPL 2.1 license.

das2pro is a pure das2 data client written in IDL with support from the Czech Institute of Atmospheric Physics. das2pro is an IDL package so it only takes a single command in IDL 8.7.1 to install a test.

das2dlm is an binary downloadable module for IDL. It is implemented in C and provides a stream format independent API. Das2dlm was created to support SPEDAS as a das2 client.

das2D provides a more natural interface for das2 data source readers written in the D supporting common D idioms such as ranges and stack-based meta-programming.

Autoplot: No list of das2 software is complete without mentioning this flexible and capable tool. Built using Java das2 display libraries, Autoplot provides fluid dataset navigation for many data sources including collections of CDF and ASCII files.