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| author | J08nY | 2025-03-20 10:24:32 +0100 |
|---|---|---|
| committer | J08nY | 2025-03-20 10:24:32 +0100 |
| commit | cf7badc004cf6c17443c850272caab9be1061e00 (patch) | |
| tree | fdcac4e968cc28bf6d5bd21d9836c73e868965ee /pyecsca/sca | |
| parent | 3169390d69e41ba07f7825efc78c86284f3cb4e1 (diff) | |
| download | pyecsca-cf7badc004cf6c17443c850272caab9be1061e00.tar.gz pyecsca-cf7badc004cf6c17443c850272caab9be1061e00.tar.zst pyecsca-cf7badc004cf6c17443c850272caab9be1061e00.zip | |
Fixup mypy.
Diffstat (limited to 'pyecsca/sca')
| -rw-r--r-- | pyecsca/sca/trace/combine.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/pyecsca/sca/trace/combine.py b/pyecsca/sca/trace/combine.py index 50a99ca..0930216 100644 --- a/pyecsca/sca/trace/combine.py +++ b/pyecsca/sca/trace/combine.py @@ -59,7 +59,7 @@ def standard_deviation(*traces: Trace) -> CombinedTrace: s = np.zeros(min_samples, dtype=np.float64) for t in traces: s = np.add(s, t.samples[:min_samples]) - s = (1 / len(traces)) * s + s *= 1 / len(traces) ts = np.zeros(min_samples, dtype=np.float64) for t in traces: d = np.subtract(t.samples[:min_samples], s) @@ -86,7 +86,7 @@ def variance(*traces: Trace) -> CombinedTrace: s = np.zeros(min_samples, dtype=np.float64) for t in traces: s = np.add(s, t.samples[:min_samples]) - s = (1 / len(traces)) * s + s *= (1 / len(traces)) ts = np.zeros(min_samples, dtype=np.float64) for t in traces: d = np.subtract(t.samples[:min_samples], s) @@ -98,7 +98,7 @@ def variance(*traces: Trace) -> CombinedTrace: @public -def average_and_variance(*traces) -> Tuple[CombinedTrace, CombinedTrace]: +def average_and_variance(*traces: Trace) -> Tuple[CombinedTrace, CombinedTrace]: """ Compute the average and sample variance of the :paramref:`~.combine.average_and_variance.traces`, sample-wise. @@ -116,7 +116,7 @@ def average_and_variance(*traces) -> Tuple[CombinedTrace, CombinedTrace]: s = np.zeros(min_samples, dtype=np.float64) for t in traces: s = np.add(s, t.samples[:min_samples]) - s = (1 / len(traces)) * s + s *= (1 / len(traces)) ts = np.zeros(min_samples, dtype=np.float64) for t in traces: d = np.subtract(t.samples[:min_samples], s) |