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import numpy as np
import pytest
from importlib_resources import files, as_file
import test.data.sca
from pyecsca.sca import (
align_correlation,
align_peaks,
align_sad,
align_dtw_scale,
align_dtw,
Trace,
InspectorTraceSet,
)
def test_align():
first_arr = np.array(
[10, 64, 120, 64, 10, 10, 10, 10, 10], dtype=np.dtype("i1")
)
second_arr = np.array([10, 10, 10, 10, 50, 80, 50, 20], dtype=np.dtype("i1"))
third_arr = np.array([70, 30, 42, 35, 28, 21, 15, 10, 5], dtype=np.dtype("i1"))
a = Trace(first_arr)
b = Trace(second_arr)
c = Trace(third_arr)
result, offsets = align_correlation(
a,
b,
c,
reference_offset=1,
reference_length=3,
max_offset=4,
min_correlation=0.65,
)
assert result is not None
assert len(result) == 2
np.testing.assert_equal(result[0].samples, first_arr)
np.testing.assert_equal(
result[1].samples,
np.array([10, 50, 80, 50, 20, 0, 0, 0], dtype=np.dtype("i1")),
)
assert len(offsets) == 2
assert offsets[0] == 0
assert offsets[1] == 3
@pytest.mark.slow
def test_large_align():
with as_file(files(test.data.sca).joinpath("example.trs")) as path:
example = InspectorTraceSet.read(path)
result, _ = align_correlation(
*example, reference_offset=100000, reference_length=20000, max_offset=15000
)
assert result is not None
@pytest.mark.slow
def test_large_dtw_align():
with as_file(files(test.data.sca).joinpath("example.trs")) as path:
example = InspectorTraceSet.read(path)
result = align_dtw(*example[:5])
assert result is not None
def test_peak_align():
first_arr = np.array(
[10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10], dtype=np.dtype("i1")
)
second_arr = np.array(
[10, 10, 10, 10, 90, 40, 50, 20, 10, 17, 16, 10], dtype=np.dtype("i1")
)
a = Trace(first_arr)
b = Trace(second_arr)
result, _ = align_peaks(
a, b, reference_offset=2, reference_length=5, max_offset=3
)
assert np.argmax(result[0].samples) == np.argmax(result[1].samples)
def test_sad_align():
first_arr = np.array(
[10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10], dtype=np.dtype("i1")
)
second_arr = np.array(
[10, 10, 90, 40, 50, 20, 10, 17, 16, 10, 10], dtype=np.dtype("i1")
)
a = Trace(first_arr)
b = Trace(second_arr)
result, _ = align_sad(
a, b, reference_offset=2, reference_length=5, max_offset=3
)
assert len(result) == 2
def test_dtw_align(plot):
first_arr = np.array(
[10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10, 8, 10, 12, 10, 13, 9],
dtype=np.dtype("i1"),
)
second_arr = np.array(
[10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10],
dtype=np.dtype("i1"),
)
third_arr = np.array(
[10, 30, 20, 21, 15, 8, 10, 47, 21, 77, 20, 28, 25, 10, 9, 10, 15, 9, 10],
dtype=np.dtype("i1"),
)
a = Trace(first_arr)
b = Trace(second_arr)
c = Trace(third_arr)
result = align_dtw(a, b, c)
assert np.argmax(result[0].samples) == np.argmax(result[1].samples)
assert np.argmax(result[1].samples) == np.argmax(result[2].samples)
plot(*result)
result_other = align_dtw(a, b, c, fast=False)
assert np.argmax(result_other[0].samples) == np.argmax(result_other[1].samples)
assert np.argmax(result_other[1].samples) == np.argmax(result_other[2].samples)
plot(*result_other)
def test_dtw_align_scale(plot):
first_arr = np.array(
[10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10, 8, 10, 12, 10, 13, 9],
dtype=np.dtype("f2"),
)
second_arr = np.array(
[10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10],
dtype=np.dtype("f2"),
)
third_arr = np.array(
[10, 30, 20, 21, 15, 8, 10, 37, 21, 77, 20, 28, 25, 10, 9, 10, 15, 9, 10],
dtype=np.dtype("f2"),
)
a = Trace(first_arr)
b = Trace(second_arr)
c = Trace(third_arr)
result = align_dtw_scale(a, b, c)
assert np.argmax(result[0].samples) == np.argmax(result[1].samples)
assert np.argmax(result[1].samples) == np.argmax(result[2].samples)
plot(*result)
result_other = align_dtw_scale(a, b, c, fast=False)
assert np.argmax(result_other[0].samples) == np.argmax(result_other[1].samples)
assert np.argmax(result_other[1].samples) == np.argmax(result_other[2].samples)
plot(*result_other)
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