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| author | J08nY | 2023-03-15 15:22:00 +0100 |
|---|---|---|
| committer | J08nY | 2023-03-15 15:22:00 +0100 |
| commit | 7d967fec195f01e73960c74bc6843cd3123d67cb (patch) | |
| tree | 9922894f5d12afd835a89996a2a84318640a08dd | |
| parent | 4cd1dc32cc87179445b3b4f377a2d3e23e9ef49b (diff) | |
| download | pyecsca-7d967fec195f01e73960c74bc6843cd3123d67cb.tar.gz pyecsca-7d967fec195f01e73960c74bc6843cd3123d67cb.tar.zst pyecsca-7d967fec195f01e73960c74bc6843cd3123d67cb.zip | |
Fix typechecks.
| -rw-r--r-- | pyecsca/sca/stacked_traces/combine.py | 20 |
1 files changed, 5 insertions, 15 deletions
diff --git a/pyecsca/sca/stacked_traces/combine.py b/pyecsca/sca/stacked_traces/combine.py index bcc90f8..f6bd738 100644 --- a/pyecsca/sca/stacked_traces/combine.py +++ b/pyecsca/sca/stacked_traces/combine.py @@ -6,7 +6,7 @@ import numpy as np from math import sqrt from public import public -from typing import Callable, Union, Tuple +from typing import Callable, Union, Tuple, cast from pyecsca.sca.trace.trace import CombinedTrace from pyecsca.sca.stacked_traces import StackedTraces @@ -158,34 +158,24 @@ class GPUTraceManager(BaseTraceManager): ) def average(self) -> CombinedTrace: - result = self._gpu_combine1D(gpu_average, 1) - assert isinstance(result, CombinedTrace) - return result + return cast(CombinedTrace, self._gpu_combine1D(gpu_average, 1)) def conditional_average(self, cond: Callable[[np.ndarray], bool]) \ -> CombinedTrace: raise NotImplementedError() def standard_deviation(self) -> CombinedTrace: - result = self._gpu_combine1D(gpu_std_dev, 1) - assert isinstance(result, CombinedTrace) - return result + return cast(CombinedTrace, self._gpu_combine1D(gpu_std_dev, 1)) def variance(self) -> CombinedTrace: - result = self._gpu_combine1D(gpu_variance, 1) - assert isinstance(result, CombinedTrace) - return result + return cast(CombinedTrace, self._gpu_combine1D(gpu_variance, 1)) def average_and_variance(self) -> Tuple[CombinedTrace, CombinedTrace]: averages, variances = self._gpu_combine1D(gpu_avg_var, 2) - assert isinstance(averages, CombinedTrace) and \ - isinstance(variances, CombinedTrace) return averages, variances def add(self) -> CombinedTrace: - result = self._gpu_combine1D(gpu_add, 1) - assert isinstance(result, CombinedTrace) - return result + return cast(CombinedTrace, self._gpu_combine1D(gpu_add, 1)) @cuda.jit(device=True) |
