pyecsca.sca.trace_set.hdf5 module¶

Provides a traceset implemented on top of the Hierarchical Data Format (HDF5).

This traceset can be loaded “inplace” which means that it is not fully loaded into memory, and only parts of traces that are operated on are in memory. This is very useful for working with huge sets of traces that do not fit in memory.

class HDF5Meta(attrs)[source]¶

Bases: MutableMapping

Metadata mapping that is HDF5-compatible (items are picklable).

clear() → None. Remove all items from D.¶

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D's items¶

keys() → a set-like object providing a view on D's keys¶

pop(k[, d]) → v, remove specified key and return the corresponding value.¶: If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair¶: as a 2-tuple; but raise KeyError if D is empty.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D¶

update([E, ]**F) → None. Update D from mapping/iterable E and F.¶: If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v