The CDF (Common Data Format) file type has become the standard interchange mechanism for sharing data in the space physics community. In addition Anaconda is a widely used python virtual environment. This repository provides a slightly altered version of the pycdf module from the SpacePy project along with Anaconda packaging for the Goddard Spaceflight Center's CDF library to create a standalone CDF reader for python.

There is no need to download and install separate CDF libraries! These are include in the package. The only dependency is numpy >= 1.11. Also, the binary CDF tools, such as cdfstats are not included. Only the components of the CDF distribution used by pycdf are part of the package.

Pre-built versions of pycdf are available from Anaconda. To install the conda package run the command:

(base) $ conda install -c dasdevelopers pycdf

If this works, then test using Van Allen Probes data, for example:

(base) $ wget https://emfisis.physics.uiowa.edu/Flight/RBSP-A/L2/2017/07/08/rbsp-a_HFR-waveform_emfisis-L2_20170708T19_v1.6.3.cdf
(base) $ python
>>> import pycdf
>>> f = pycdf.CDF('rbsp-a_HFR-waveform_emfisis-L2_20170708T19_v1.6.3.cdf')
>>> f.keys()

If this produces a list similar to the following...

KeysView(<CDF:
APID: CDF_UINT2 [634]
Epoch: CDF_TIME_TT2000 [634]
HBGain: CDF_BYTE [634]
HBSelect: CDF_BYTE [634]
HFR_Spec: CDF_FLOAT [0, 4096]
HFRsamples: CDF_REAL4 [634, 4096]
MET: CDF_REAL8 [634]
SPTT: CDF_TIME_TT2000 [634]
fftSize: CDF_INT4 [1] NRV
timeOffsets: CDF_REAL8 [4096] NRV
>)

... then it works.

For more information on using pycdf, see the SpacePy pycdf webpage.

If this particular dataset is of interest, then see the Van Allen Probes EMFISIS instrument data site.

Newer MacOS NumPy packages (> 1.17.3) require CPUs which support AVX features (see Anaconda issue #9678 ) and thus they will not run on older (2011 era) Macs. To keep this package usable by older Mac's the maximum NumPy version supported is 1.17.3.

These instructions are only for package manatainers, though anyone can be a package maintainer, so dive in :)

First, activate your conda environment:

$ source $HOME/minconda3/bin/activate  # For ex. varies by install location

Install the conda-build, conda-verify, and anaconda-client packages if needed

(base) $ conda install conda-build
(base) $ conda install conda-verify
(base) $ conda install anaconda-client
(base) $ conda install m2-patch         # Windows only

In the working directory of this repo run the build command

(base) $ conda-build ./recipe

The build command downloads the CDF software from the Goddard site and then patches the sources to cut out some build commands and to add in the python wrapper supplied by SpacePy.

If you change the contents of the ./pycdf subdirectory or the setup.py file then you will have to rebuild the patch file. To rebuild the patch file, run the command:

$ ./make_patch.sh

The script requires bash, diff, sed, and wget for proper operation. This will update the file recipe/0001_add_pycdf.patch.

Upload the build output to your favorite repository. Below I'm using DasDevelopers site at anaconda.org.

(base) $ anaconda upload -u dasdevelopers pycdf

This repo is just a repackaging of other people's hard work. Hats off to the crew that put together the initial CDF specification and libraries at GSFC. The format they designed strikes a nice balance between generality and simplicity. Also, to the SpacePy project which produced an elegant python CDF wrapper.