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# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file.
"""Unit tests for 2D-array function checks decorators."""
import numpy as np
import pytest
from sigima.tools.checks import check_2d_array
@check_2d_array(dtype=np.floating)
def identity(data: np.ndarray) -> np.ndarray:
"""Dummy image function returning input."""
return data
def test_valid_2d_float_input() -> None:
"""Test with valid 2D float array."""
data = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
result = identity(data)
np.testing.assert_array_equal(result, data)
def test_wrong_ndim() -> None:
"""Test with non-2D input."""
data = np.array([1.0, 2.0, 3.0], dtype=float) # 1D
with pytest.raises(ValueError, match="Input array must be 2D"):
identity(data)
def test_wrong_dtype() -> None:
"""Test with wrong dtype."""
data = np.array([[1, 2], [3, 4]], dtype=int)
with pytest.raises(
TypeError, match="Input array must be of type <class 'numpy.floating'>"
):
identity(data)
@check_2d_array(non_constant=True)
def normalize(data: np.ndarray) -> np.ndarray:
"""Normalize 2D array to range [0, 1]."""
return data / np.nanmax(data)
def test_non_constant_error() -> None:
"""Test with non-constant input."""
data = np.full((3, 3), 5.0)
with pytest.raises(ValueError, match="Input array has no dynamic range."):
normalize(data)
@check_2d_array(finite_only=True)
def sum_image(data: np.ndarray) -> float:
"""Sum all finite values in a 2D array."""
return np.sum(data)
def test_non_finite_values() -> None:
"""Test with non-finite values."""
data = np.array([[1.0, np.inf], [3.0, np.nan]])
with pytest.raises(ValueError, match="Input array contains non-finite values."):
sum_image(data)
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