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Fix out of bounds segfault #272

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Jul 15, 2024
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3 changes: 3 additions & 0 deletions .github/workflows/e2e_testing.yml
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,9 @@ jobs:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
NEPTUNE_API_TOKEN: ${{ secrets.NEPTUNE_E2E_TOKEN }}
NEPTUNE_PROJECT_NAME: "MannLabs/alphaDIA-e2e-tests"
NUMBA_BOUNDSCHECK: 1
NUMBA_DEVELOPER_MODE: 1
NUMBA_FULL_TRACEBACKS: 1
steps:
- uses: actions/checkout@v4
- name: Conda info
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79 changes: 75 additions & 4 deletions alphadia/features.py
Original file line number Diff line number Diff line change
Expand Up @@ -352,8 +352,19 @@ def center_envelope(x):
) * 0.5


@nb.njit
def center_envelope_1d(x):
@nb.njit(inline="always")
def _odd_center_envelope(x: np.ndarray):
"""
Applies an interference correction envelope to a collection of odd-length 1D arrays.
Numba function which operates in place.

Parameters
----------
x: np.ndarray
Array of shape (a, b) where a is the number of arrays and b is the length of each array.
It is mandatory that dimension b is odd.

"""
center_index = x.shape[1] // 2

for a0 in range(x.shape[0]):
Expand All @@ -362,16 +373,76 @@ def center_envelope_1d(x):

for i in range(1, center_index + 1):
x[a0, center_index - i] = min(left_intensity, x[a0, center_index - i])

left_intensity = (
x[a0, center_index - i] + x[a0, center_index - i - 1]
x[a0, center_index - i] + x[a0, center_index - i + 1]
) * 0.5

x[a0, center_index + i] = min(right_intensity, x[a0, center_index + i])
right_intensity = (
x[a0, center_index + i] + x[a0, center_index + i + 1]
x[a0, center_index + i] + x[a0, center_index + i - 1]
) * 0.5


@nb.njit(inline="always")
def _even_center_envelope(x: np.ndarray):
"""
Applies an interference correction envelope to a collection of even-length 1D arrays.
Numba function which operates in place.

Parameters
----------
x: np.ndarray
Array of shape (a, b) where a is the number of arrays and b is the length of each array.
It is mandatory that dimension b is even.

"""
center_index_right = x.shape[1] // 2
center_index_left = center_index_right - 1

for a0 in range(x.shape[0]):
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left_intensity = x[a0, center_index_left]
right_intensity = x[a0, center_index_right]

for i in range(1, center_index_left + 1):
x[a0, center_index_left - i] = min(
left_intensity, x[a0, center_index_left - i]
)

left_intensity = (
x[a0, center_index_left - i] + x[a0, center_index_left - i + 1]
) * 0.5

x[a0, center_index_right + i] = min(
right_intensity, x[a0, center_index_right + i]
)
right_intensity = (
x[a0, center_index_right + i] + x[a0, center_index_right + i - 1]
) * 0.5


@nb.njit
def center_envelope_1d(x: np.ndarray):
"""
Applies an interference correction envelope to a collection of 1D arrays.
Numba function which operates in place.

Parameters
----------
x: np.ndarray
Array of shape (a, b) where a is the number of arrays and b is the length of each array.
It is mandatory that dimension b is odd.

"""

is_even = x.shape[1] % 2 == 0

if is_even:
_even_center_envelope(x)
else:
_odd_center_envelope(x)


@nb.njit
def weighted_mean_a1(array, weight_mask):
"""
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3 changes: 3 additions & 0 deletions alphadia/plexscoring.py
Original file line number Diff line number Diff line change
Expand Up @@ -1895,6 +1895,9 @@ def __call__(
)
thread_count = 1 if debug else thread_count

if debug:
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logger.info("Debug mode enabled. Processing only 10 elution groups")

alphatims.utils.set_threads(thread_count)
_executor(
range(iterator_len),
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5 changes: 4 additions & 1 deletion tests/unit_tests/conftest.py
Original file line number Diff line number Diff line change
Expand Up @@ -188,7 +188,10 @@ def pytest_configure(config):
]
pytest.test_data[raw_folder] = raw_files

# important to supress matplotlib output
# set numba environment variables
os.environ["NUMBA_BOUNDSCHECK"] = "1"
os.environ["NUMBA_DEVELOPER_MODE"] = "1"
os.environ["NUMBA_FULL_TRACEBACKS"] = "1"


def random_tempfolder():
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79 changes: 79 additions & 0 deletions tests/unit_tests/test_features.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,79 @@
import numpy as np
import pytest

from alphadia.features import center_envelope_1d


@pytest.mark.parametrize(
"input_array, expected_output",
[
(
np.array([[1, 1, 1, 1, 1, 1, 1]], dtype=np.float64),
np.array(
[
[1, 1, 1, 1, 1, 1, 1],
],
dtype=np.float64,
),
),
(
np.array([[100, 10, 1, 1, 1, 10, 100]], dtype=np.float64),
np.array([[1, 1, 1, 1, 1, 1, 1]], dtype=np.float64),
),
(
np.array([[100, 0, 0, 1, 0, 0, 100]], dtype=np.float64),
np.array([[0, 0, 0, 1, 0, 0, 0]], dtype=np.float64),
),
(
np.array([[1, 1, 1, 1, 1, 1, 1, 1]], dtype=np.float64),
np.array(
[
[1, 1, 1, 1, 1, 1, 1, 1],
],
dtype=np.float64,
),
),
(
np.array([[100, 10, 1, 1, 1, 1, 10, 100]], dtype=np.float64),
np.array([[1, 1, 1, 1, 1, 1, 1, 1]], dtype=np.float64),
),
(
np.array([[100, 0, 0, 1, 1, 0, 0, 100]], dtype=np.float64),
np.array([[0, 0, 0, 1, 1, 0, 0, 0]], dtype=np.float64),
),
],
)
def test_center_envelope_1d_simple(input_array, expected_output):
# given

# when
center_envelope_1d(input_array)

# then
np.testing.assert_array_almost_equal(input_array, expected_output)


def test_center_envelope_1d_multiple_rows():
# given
shape = (10, 11)

input_array = np.random.rand(*shape)
output_array = input_array.copy()
# when
center_envelope_1d(input_array)

# then
assert output_array.shape == input_array.shape
assert np.all(input_array[:, 0] <= output_array[:, 0])
assert np.all(input_array[:, -1] <= output_array[:, -1])


def test_center_envelope_1d_empty_array():
# given
x = np.array([[]], dtype=np.float64)

# when
center_envelope_1d(x)

# then
assert x.shape == (1, 0)
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