02-hdf5-container.py

# When performing side-channel analysis, a user will seek to store its data for
# further usages. To our knowledge, every lab has its own format for storing
# side-channel traces.
#
# The probably most popular traces storage file format is hdf5 (Hierarchical
# Data Format, see: https://www.hdfgroup.org/HDF5/). For each set of traces, a
# single hdf5 file is created, implementing two datasets: the first one for
# leakages, and the second for values.
#
# Lascar provides the class `Hdf5Container` which allows handling this format
# transparently. This enables working on traces without having to load them all
# in memory (as a `TraceBatchContainer` would do).
#
# The `Hdf5Container.export` method can be used to convert any Container into
# a `Hdf5Container` (i.e. by creating a file containing all its traces).
#
# In the following example, a TraceBatchContainer is created, and converted into
# a `Hdf5Container`.

from lascar import TraceBatchContainer, Hdf5Container
import numpy as np

leakages = np.random.rand(10, 100)  # 10 leakages, 100 time samples each.
values = np.random.randint(0, 256, (10, 16))  # 10 associated values, 16 bytes each.
batch = TraceBatchContainer(leakages, values)
hdf5 = Hdf5Container.export(batch, "tmp.h5")

# Since Hdf5Container is a Container, it implements all the features seen before.
# This can be verified as follows:

for (a, b) in zip(batch, hdf5, strict=True):
    assert a == b