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# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file.
"""
Image peak detection test
"""
# pylint: disable=invalid-name # Allows short reference names like x, y, ...
# pylint: disable=duplicate-code
from __future__ import annotations
import time
import numpy as np
import pytest
import sigima.enums
import sigima.objects
import sigima.params
import sigima.proc.image
from sigima.tests import guiutils
from sigima.tests.data import get_peak2d_data
from sigima.tests.env import execenv
from sigima.tests.helpers import check_array_result, validate_detection_rois
from sigima.tools.image import get_2d_peaks_coords
def exec_image_peak_detection_func(data: np.ndarray) -> np.ndarray:
"""Execute image peak detection function
Args:
data: 2D image data
Returns:
2D array of peak coordinates
"""
t0 = time.time()
coords = get_2d_peaks_coords(data)
dt = time.time() - t0
execenv.print(f"Calculation time: {int(dt * 1e3):d} ms")
execenv.print(f" => {coords.tolist()}")
return coords
def view_image_peak_detection(data: np.ndarray, coords: np.ndarray) -> None:
"""View image peak detection results
Args:
data: 2D image data
coords: Coordinates of detected peaks (shape: (n, 2))
"""
# pylint: disable=import-outside-toplevel
from sigima import viz
execenv.print("Peak detection results:")
items = [viz.create_image(data, colormap="hsv")]
for x, y in coords:
items.append(viz.create_marker(x, y))
viz.view_image_items(
items, name=view_image_peak_detection.__name__, title="Peak Detection"
)
def test_peak2d_unit():
"""2D peak detection unit test"""
data, coords_expected = get_peak2d_data(seed=1, multi=False)
coords = exec_image_peak_detection_func(data)
assert coords.shape == coords_expected.shape, (
f"Expected {coords_expected.shape[0]} peaks, got {coords.shape[0]}"
)
# Absolute tolerance is set to 2 pixels, as coordinates are in pixel units
# and the algorithm may detect peaks at slightly different pixel locations
# Convert coordinates to float64 for dtype compatibility with expected results
coords_float = coords.astype(np.float64)
check_array_result(
"Peak coords (sigima.tools.image.)",
coords_float,
coords_expected,
atol=2,
sort=True,
)
@pytest.mark.validation
def test_image_peak_detection():
"""2D peak detection unit test"""
data, coords_expected = get_peak2d_data(seed=1, multi=False)
for create_rois in (True, False):
for roi_geometry in sigima.enums.DetectionROIGeometry:
if (
not create_rois
and roi_geometry != sigima.enums.DetectionROIGeometry.RECTANGLE
):
continue
obj = sigima.objects.create_image("peak2d_unit_test", data=data)
param = sigima.params.Peak2DDetectionParam.create(
create_rois=create_rois, roi_geometry=roi_geometry
)
geometry = sigima.proc.image.peak_detection(obj, param)
# Apply ROIs from detection result
sigima.proc.image.apply_detection_rois(obj, geometry)
coords = geometry.coords
assert coords.shape == coords_expected.shape, (
f"Expected {coords_expected.shape[0]} peaks, got {coords.shape[0]}"
)
# Absolute tolerance is set to 2 pixels, as coordinates are in pixel units
# and the algorithm may detect peaks at slightly different pixel locations
check_array_result(
"Peak coords (comp.)", coords, coords_expected, atol=2, sort=True
)
# Validate ROI creation
validate_detection_rois(obj, coords, create_rois, roi_geometry)
@pytest.mark.gui
def test_peak2d_interactive():
"""2D peak detection interactive test"""
data, _coords = get_peak2d_data(multi=False)
coords = exec_image_peak_detection_func(data)
with guiutils.lazy_qt_app_context(force=True):
view_image_peak_detection(data, coords)
if __name__ == "__main__":
test_peak2d_unit()
test_image_peak_detection()
test_peak2d_interactive()
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