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import numpy as np
import pytest
from pyecsca.sca import (
Trace,
absolute,
invert,
threshold,
rolling_mean,
offset,
recenter,
normalize,
normalize_wl,
transform
)
@pytest.fixture()
def trace():
return Trace(np.array([30, -60, 145, 247], dtype=np.dtype("i2")), None)
def test_absolute(trace):
result = absolute(trace)
assert result is not None
assert result.samples[1] == 60
def test_invert(trace):
result = invert(trace)
assert result is not None
np.testing.assert_equal(result.samples, [-30, 60, -145, -247])
def test_threshold(trace):
result = threshold(trace, 128)
assert result is not None
assert result.samples[0] == 0
assert result.samples[2] == 1
def test_rolling_mean(trace):
result = rolling_mean(trace, 2)
assert result is not None
assert len(result.samples) == 3
assert result.samples[0] == -15
assert result.samples[1] == 42.5
assert result.samples[2] == 196
def test_offset(trace):
result = offset(trace, 5)
assert result is not None
np.testing.assert_equal(
result.samples, np.array([35, -55, 150, 252], dtype=np.dtype("i2"))
)
def test_recenter(trace):
assert recenter(trace) is not None
def test_normalize(trace):
result = normalize(trace)
assert result is not None
assert np.isclose(0, np.mean(result.samples))
assert np.isclose(1, np.var(result.samples))
def test_normalize_wl(trace):
result = normalize_wl(trace)
assert result is not None
assert np.isclose(0, np.mean(result.samples))
assert np.isclose(1/len(result), np.std(result.samples))
def test_transform(trace):
result = transform(trace, 5, 10)
assert result is not None
assert min(result) == 5
assert max(result) == 10
|
