Scientific Data Format for Python

SDF is a Python package to read, write and interpolate multi-dimensional data. The Scientific Data Format is an open file format based on HDF5 to store multi-dimensional data such as parameters, simulation results or measurements. It supports...

• very large files
• up to 32 dimensions
• hierarchical structure
• units, comments and custom meta-information

For detailed information see the SDF specification.

Installation

To install the latest release from PyPI or update an existing installation:

python -m pip install --upgrade sdf

Tutorial

Import the SDF and NumPy packages:

>>> import sdf
>>> import numpy as np

Create the data arrays:

>>> t = np.linspace(0, 10, 51)
>>> v = np.sin(t)

Create the datasets:

>>> ds_t = sdf.Dataset('t', data=t, unit='s', is_scale=True, display_name='Time')
>>> ds_v = sdf.Dataset('v', data=v, unit='V', scales=[ds_t])

Create the root group and write the file:

>>> g = sdf.Group('/', comment='A sine voltage', datasets=[ds_t, ds_v])
>>> sdf.save('sine.sdf', g)

Read the dataset from the SDF file asserting the correct unit of the dataset and scale:

>>> ds_v2 = sdf.load('sine.sdf', '/v', unit='V', scale_units=['s'])

Get the meta info and data array from the dataset:

>>> ds_v2.unit
'V'
>>> ds_v2.data.shape
(51,)

Get the scale for the first dimension:

>>> ds_t2 = ds_v2.scales[0]
>>> ds_t2.unit
's'

License

The code is released under the 2-Clause BSD license.