diff options
Diffstat (limited to 'pyecsca/sca/trace/process.py')
| -rw-r--r-- | pyecsca/sca/trace/process.py | 22 |
1 files changed, 10 insertions, 12 deletions
diff --git a/pyecsca/sca/trace/process.py b/pyecsca/sca/trace/process.py index 8e983b2..4cdbeff 100644 --- a/pyecsca/sca/trace/process.py +++ b/pyecsca/sca/trace/process.py @@ -13,7 +13,7 @@ def absolute(trace: Trace) -> Trace: :param trace: :return: """ - return Trace(copy(trace.title), copy(trace.data), np.absolute(trace.samples)) + return Trace(np.absolute(trace.samples), copy(trace.title), copy(trace.data)) @public @@ -24,7 +24,7 @@ def invert(trace: Trace) -> Trace: :param trace: :return: """ - return Trace(copy(trace.title), copy(trace.data), np.negative(trace.samples)) + return Trace(np.negative(trace.samples), copy(trace.title), copy(trace.data)) @public @@ -39,7 +39,7 @@ def threshold(trace: Trace, value) -> Trace: result_samples = trace.samples.copy() result_samples[result_samples <= value] = 0 result_samples[np.nonzero(result_samples)] = 1 - return Trace(copy(trace.title), copy(trace.data), result_samples) + return Trace(result_samples, copy(trace.title), copy(trace.data)) def rolling_window(samples: np.ndarray, window: int) -> np.ndarray: @@ -57,9 +57,8 @@ def rolling_mean(trace: Trace, window: int) -> Trace: :param window: :return: """ - return Trace(copy(trace.title), copy(trace.data), - np.mean(rolling_window(trace.samples, window), -1).astype( - dtype=trace.samples.dtype)) + return Trace(np.mean(rolling_window(trace.samples, window), -1).astype( + dtype=trace.samples.dtype), copy(trace.title), copy(trace.data)) @public @@ -71,7 +70,7 @@ def offset(trace: Trace, offset) -> Trace: :param offset: :return: """ - return Trace(copy(trace.title), copy(trace.data), trace.samples + offset) + return Trace(trace.samples + offset, copy(trace.title), copy(trace.data)) def root_mean_square(trace: Trace): @@ -92,12 +91,11 @@ def recenter(trace: Trace) -> Trace: @public def normalize(trace: Trace) -> Trace: - return Trace(copy(trace.title), copy(trace.data), - (trace.samples - np.mean(trace.samples)) / np.std(trace.samples)) + return Trace((trace.samples - np.mean(trace.samples)) / np.std(trace.samples), + copy(trace.title), copy(trace.data)) @public def normalize_wl(trace: Trace) -> Trace: - return Trace(copy(trace.title), copy(trace.data), - (trace.samples - np.mean(trace.samples)) / ( - np.std(trace.samples) * len(trace.samples))) + return Trace((trace.samples - np.mean(trace.samples)) / ( + np.std(trace.samples) * len(trace.samples)), copy(trace.title), copy(trace.data)) |