Commit 7ce760f4 authored by Aurelien Vasselle's avatar Aurelien Vasselle Committed by Rémi Huguet
Browse files

fix: improve string representation performance of Container object

parent ffb0150e

scared/container.py

+1 −1
Original line number Diff line number Diff line
@@ -114,7 +114,7 @@ class Container: 
    def __str__(self):

        template_str = f'''Traces container:

    Number of traces: {len(self._ths)}

    Traces size     : {self._ths.samples.shape[1]}

    Traces size     : {len(self._ths.samples[0])}

    Metadata        : {list(self._ths.metadatas.keys())}

    Frame           : {self._frame_str}

    Preprocesses    : {[p.__name__ for p in self.preprocesses] if len(self.preprocesses) > 0 else 'None'}

scared/distinguishers/base.py

+1 −1
Original line number Diff line number Diff line
@@ -87,7 +87,7 @@ class DistinguisherMixin(abc.ABC): 
            logger.debug(f'Needed memory estimated to {needed_mem} GB, for available {available_mem}.')

            self._is_checked = True

            if needed_mem > 0.9 * available_mem:

                raise MemoryError(

                raise DistinguisherError(

                    f'This analysis will probably need more than 90% of your available memory - {available_mem} GB available against {needed_mem} GB needed.'

                )

scared/distinguishers/cpa.py

+2 −3
Original line number Diff line number Diff line 
from .base import _StandaloneDistinguisher, DistinguisherMixin, DistinguisherError

import numpy as _np

import logging



logger = logging.getLogger(__name__)
@@ -26,8 +25,8 @@ class CPADistinguisherMixin(DistinguisherMixin): 
            self.ey = _np.zeros((data_words), dtype=self.precision)

            self.ey2 = _np.zeros((data_words), dtype=self.precision)

            self.exy = _np.zeros((data_words, trace_size), dtype=self.precision)

        except (ValueError, MemoryError) as e:

            raise type(e)(f'Trace size and data words are too large to proceed with accumulation for CPA {e}.')

        except ValueError as e:

            raise ValueError(f'Trace size and data words are too large to proceed with accumulation for CPA: {e}')



    def _update(self, traces, data):

        if traces.shape[1] != self.ex.shape[0]:

scared/distinguishers/dpa.py

+4 −2
Original line number Diff line number Diff line
@@ -27,8 +27,10 @@ class DPADistinguisherMixin(DistinguisherMixin): 
            self.accumulator_traces = _np.zeros((trace_size), dtype=self.precision)

            self.accumulator_ones = _np.zeros((data_words, trace_size), dtype=self.precision)

            self.processed_ones = _np.zeros((data_words), dtype='uint32')

        except (ValueError, MemoryError) as e:

            raise type(e)(f'Trace size and data words are too large to proceed with accumulation for DPA {e}')

        except ValueError as e:

            raise ValueError(f'Trace size and data words are too large to proceed with accumulation for DPA: {e}.')

        except MemoryError as e:

            raise MemoryError(f'Trace size and data words results in too large intermediate state to proceed with accumulation for DPA as {e}.')



    def _update(self, traces, data):

        if traces.shape[1] != self.accumulator_traces.shape[0]:

scared/distinguishers/partitioned.py

+1 −4
Original line number Diff line number Diff line
@@ -22,10 +22,7 @@ class _PartitionnedDistinguisherBaseMixin(DistinguisherMixin): 
            self.partitions = range(r)

        self._trace_length = traces.shape[1]

        self._data_words = data.shape[1]

        try:

        self._initialize_accumulators()

        except MemoryError:

            raise MemoryError(f'Trace size and data words are too large to proceed with accumulation.')



    def _update(self, traces, data):

        if traces.shape[1] != self._trace_length: