Python ISTP loader

An easy to use loader for ISTP-compliant CDF and NetCDF files, as commonly distributed by CDAWeb, AMDA and other space-physics data archives.

Rather than exposing raw variables, PyISTP reads the ISTP metadata conventions (VAR_TYPE, DEPEND_n, *_PTR, LABLAXIS, ...) and hands you each data variable together with its resolved axes (time and other support variables), labels and attributes.

• Free software: GNU General Public License v3
• Documentation: https://pyistp.readthedocs.io.

• Loads ISTP-compliant CDF files (via pycdfpp by default, or spacepy).
• Loads ISTP-compliant NetCDF files (via netCDF4).
• Reads from a file path or directly from an in-memory bytes buffer (handy for data fetched over HTTP).
• Supports a separate master/skeleton file holding the metadata while the values come from the data file.
• Automatically resolves DEPEND_n support variables into axes, with fallback to the master file.
• Converts CDF epoch types and NetCDF CF/Unix time variables to numpy.datetime64[ns].
• Lazily materializes variable values (the array is read on first access).
• Tolerates many non-ISTP-compliant files (CDAWeb, Cluster/CSA) with warnings rather than failures.

pip install pyistp

The default CDF backend is pycdfpp; spacepy is used as a fallback if available. NetCDF support requires netCDF4. To force a specific CDF backend, set the PYISTP_CDFLIB environment variable to pycdfpp or spacepy.

Load a file and inspect its data variables:

import pyistp
istp = pyistp.load(file="wi_k0_mfi_20220101_v01.cdf")
istp.data_variables() # -> ['BGSEc', 'BF1', 'PGSM', ...]
istp.attributes() # global attribute names
var = istp.data_variable("BGSEc")
var.values # numpy array of values (read lazily)
var.axes[0].values # the time axis (numpy.datetime64[ns])
var.attributes # variable attributes
var.labels # component labels, if any

Load directly from a buffer, for instance data fetched over HTTP:

import requests, pyistp
raw = requests.get(
 "https://spdf.gsfc.nasa.gov/pub/data/themis/thc/l2/efi/2020/"
 "thc_l2_efi_20200101_v01.cdf").content
istp = pyistp.load(buffer=raw)
var = istp.data_variable("thc_eff_dot0_gsm")
import matplotlib.pyplot as plt
plt.plot(var.axes[0].values, var.values)

Use a separate master/skeleton file for the metadata:

istp = pyistp.load(file="data.cdf", master_file="skeleton.cdf")
# or from buffers:
istp = pyistp.load(buffer=data_bytes, master_buffer=skeleton_bytes)

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.