diff --git a/README.md b/README.md index 2eb2537..fe2c11f 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # ZedProfiler -[![Coverage](https://img.shields.io/badge/coverage-87%25-green)](#quality-gates) +[![Coverage](https://img.shields.io/badge/coverage-99%25-brightgreen)](#quality-gates) CPU-first 3D image feature extraction toolkit for high-content and high-throughput image-based profiling. @@ -18,12 +18,55 @@ just env ## Quick usage (API shape) ```python -from zedprofiler import colocalization # promoted convenience import -from zedprofiler.featurization import texture # stays in feature namespace - -# Implementation is scaffolded in PR 1 and will be completed in module PRs. -result = colocalization.compute() -texture_result = texture.compute() +import os +import pathlib +import pandas as pd + +from zedprofiler.IO.loading_classes import ImageSetConfig, ImageSetLoader, ObjectLoader +from zedprofiler.featurization.areasizeshape import compute as compute_areasizeshape + +image_set_path = pathlib.Path( + os.path.expanduser( + "~/mnt/bandicoot/NF1_organoid_data/data/NF0014_T1/zstack_images/C2-1/" + ) + ).resolve(strict=True) +mask_set_path = pathlib.Path( + os.path.expanduser( + "~/mnt/bandicoot/NF1_organoid_data/data/NF0014_T1/segmentation_masks/C2-1/" + ) + ).resolve(strict=True) +image_set_config = ImageSetConfig( + image_set_name="test_set", + raw_image_key_name=["AGP"], + mask_key_name=["Nuclei"], +) +image_set_loader = ImageSetLoader( + image_set_path=image_set_path, + mask_set_path=mask_set_path, + anisotropy_spacing=(1,0.1,0.1), + channel_mapping={ + "DNA": 405, + "ER": 488, + "AGP": 555, + "Mito": 640, + "Organoid": "organoid_", + "Cell": "cell_", + "Nuclei": "nuclei_", + "Cytoplasm": "cytoplasm_", + }, + config=image_set_config +) + +object_loader = ObjectLoader( + image_set_loader=image_set_loader, + channel_name=image_set_config.raw_image_key_name[0], + compartment_name=image_set_config.mask_key_name[0], +) +area_dict_df = pd.DataFrame(compute_areasizeshape( + image_set_loader=image_set_loader, + object_loader=object_loader, +)) +area_dict_df ``` ## Data Contract diff --git a/ROADMAP.md b/ROADMAP.md index 99f0134..9252466 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -93,6 +93,11 @@ The roadmap is intended to be a living document and may be updated as needed. - [ ] Changelog, semantic tag, PyPI publish automation, README install updates. +### Phase 4: Post-release improvements (PR 14+) + +14. Add the ability for loading of images from array instead of file + file paths for increased flexibility in data sources and testing. + ## Verification Gates - [ ] Run full unit and integration tests on Linux with coverage >=85%. diff --git a/pyproject.toml b/pyproject.toml index 811b86e..ffabff8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,7 +19,10 @@ classifiers = [ dependencies = [ "fire>=0.7.1", "jinja2>=3.1.6", + "numpy>=1.26", "pandas>=3.0.2", + "pyarrow>=16", + "scikit-image>=0.24", ] scripts.ZedProfiler = "ZedProfiler.cli:trigger" diff --git a/src/zedprofiler/featurization/__init__.py b/src/zedprofiler/featurization/__init__.py index df017b7..34fadf9 100644 --- a/src/zedprofiler/featurization/__init__.py +++ b/src/zedprofiler/featurization/__init__.py @@ -4,7 +4,14 @@ modules to be promoted at the package top-level. """ -from . import areasizeshape, colocalization, granularity, intensity, neighbors, texture +from . import ( + areasizeshape, + colocalization, + granularity, + intensity, + neighbors, + texture, +) __all__ = [ "areasizeshape", diff --git a/src/zedprofiler/featurization/areasizeshape.py b/src/zedprofiler/featurization/areasizeshape.py index f482c3a..403da6d 100644 --- a/src/zedprofiler/featurization/areasizeshape.py +++ b/src/zedprofiler/featurization/areasizeshape.py @@ -1,10 +1,168 @@ -"""Area/size/shape featurization module scaffold.""" +"""Area, size, and shape features for 3D objects.""" from __future__ import annotations +from collections.abc import Sequence +from importlib import import_module +from typing import Protocol + +import numpy as np + from zedprofiler.exceptions import ZedProfilerError -def compute() -> dict[str, list[float]]: - """Placeholder for area/size/shape computation implementation.""" - raise ZedProfilerError("areasizeshape.compute is not implemented yet") +class SupportsImageSetLoader(Protocol): + """Minimal image-set loader interface required by this module.""" + + anisotropy_spacing: tuple[float, float, float] + + +class SupportsObjectLoader(Protocol): + """Minimal object loader interface required by this module.""" + + label_image: np.ndarray + object_ids: Sequence[int] + + +def _empty_feature_result() -> dict[str, list[float]]: + """Return deterministic empty output schema for area/size/shape features.""" + return { + "object_id": [], + "Volume": [], + "CenterX": [], + "CenterY": [], + "CenterZ": [], + "BboxVolume": [], + "MinX": [], + "MaxX": [], + "MinY": [], + "MaxY": [], + "MinZ": [], + "MaxZ": [], + "Extent": [], + "EulerNumber": [], + "EquivalentDiameter": [], + "SurfaceArea": [], + } + + +def compute( + image_set_loader: SupportsImageSetLoader | None = None, + object_loader: SupportsObjectLoader | None = None, +) -> dict[str, list[float]]: + """Compute area/size/shape features for one object loader. + + This supports two invocation modes: + - no arguments: returns an empty deterministic schema so dispatchers can + call the function without crashing. + - both loaders provided: executes feature extraction. + """ + if image_set_loader is None and object_loader is None: + return _empty_feature_result() + if image_set_loader is None or object_loader is None: + raise ZedProfilerError( + "areasizeshape.compute requires both image_set_loader and " + "object_loader for execution." + ) + + return measure_3D_area_size_shape( + image_set_loader=image_set_loader, + object_loader=object_loader, + ) + + +def _get_skimage_measure() -> object: + """Return `skimage.measure` or raise a user-facing dependency error.""" + try: + return import_module("skimage.measure") + except ImportError as exc: + raise ZedProfilerError( + "areasizeshape requires scikit-image for area/size/shape computation." + ) from exc + + +def calculate_surface_area( + label_object: np.ndarray, + props: dict[str, np.ndarray], + spacing: tuple[float, float, float], +) -> float: + """Calculate surface area for one labeled object using marching cubes.""" + measure = _get_skimage_measure() + + volume = label_object[ + max(props["bbox-0"][0], 0) : min(props["bbox-3"][0], label_object.shape[0]), + max(props["bbox-1"][0], 0) : min(props["bbox-4"][0], label_object.shape[1]), + max(props["bbox-2"][0], 0) : min(props["bbox-5"][0], label_object.shape[2]), + ] + volume_truths = volume > 0 + verts, faces, _normals, _values = measure.marching_cubes( + volume_truths, + method="lewiner", + spacing=spacing, + level=0, + ) + return measure.mesh_surface_area(verts, faces) + + +def measure_3D_area_size_shape( + image_set_loader: SupportsImageSetLoader, + object_loader: SupportsObjectLoader, +) -> dict[str, list[float]]: + """Measure area/size/shape features for each non-zero label object.""" + measure = _get_skimage_measure() + + label_object = object_loader.label_image + spacing = image_set_loader.anisotropy_spacing + unique_objects = object_loader.object_ids + + features_to_record = _empty_feature_result() + + desired_properties = [ + "area", + "bbox", + "centroid", + "bbox_area", + "extent", + "euler_number", + "equivalent_diameter", + ] + for label in unique_objects: + if label == 0: + continue + subset_lab_object = label_object.copy() + subset_lab_object[subset_lab_object != label] = 0 + props = measure.regionprops_table( + subset_lab_object, + properties=desired_properties, + ) + + features_to_record["object_id"].append(label) + features_to_record["Volume"].append(props["area"].item()) + features_to_record["CenterX"].append(props["centroid-2"].item()) + features_to_record["CenterY"].append(props["centroid-1"].item()) + features_to_record["CenterZ"].append(props["centroid-0"].item()) + features_to_record["BboxVolume"].append(props["bbox_area"].item()) + features_to_record["MinX"].append(props["bbox-2"].item()) + features_to_record["MaxX"].append(props["bbox-5"].item()) + features_to_record["MinY"].append(props["bbox-1"].item()) + features_to_record["MaxY"].append(props["bbox-4"].item()) + features_to_record["MinZ"].append(props["bbox-0"].item()) + features_to_record["MaxZ"].append(props["bbox-3"].item()) + features_to_record["Extent"].append(props["extent"].item()) + features_to_record["EulerNumber"].append(props["euler_number"].item()) + features_to_record["EquivalentDiameter"].append( + props["equivalent_diameter"].item() + ) + + try: + features_to_record["SurfaceArea"].append( + calculate_surface_area( + label_object=label_object, + props=props, + spacing=spacing, + ) + ) + except (RuntimeError, ValueError): + features_to_record["SurfaceArea"].append(np.nan) + + return features_to_record diff --git a/tests/featurization/test_areasizeshape.py b/tests/featurization/test_areasizeshape.py new file mode 100644 index 0000000..f72714b --- /dev/null +++ b/tests/featurization/test_areasizeshape.py @@ -0,0 +1,338 @@ +"""Tests for areasizeshape module compute behavior.""" + +from __future__ import annotations + +from typing import ClassVar + +import numpy as np +import pytest + +from zedprofiler.exceptions import ZedProfilerError +from zedprofiler.featurization import areasizeshape + +# Test constants for coordinate ranges and object counts +NUM_TEST_OBJECTS = 2 +COORD_LOWER_BOUND = 1 +COORD_UPPER_BOUND = 3 +EXTENT_LOWER_BOUND = 0 +EXTENT_UPPER_BOUND = 1 + + +class DummyImageSetLoader: + """Minimal image set loader double for compute tests.""" + + anisotropy_spacing = (1.0, 1.0, 1.0) + + +class DummyObjectLoader: + """Minimal object loader double for compute tests.""" + + label_image = np.zeros((3, 3, 3), dtype=np.int32) + object_ids: ClassVar = [0] + + +def test_compute_no_args_returns_empty_schema() -> None: + """No-arg compute should be callable and return deterministic keys.""" + result = areasizeshape.compute() + + assert isinstance(result, dict) + assert list(result.keys()) == [ + "object_id", + "Volume", + "CenterX", + "CenterY", + "CenterZ", + "BboxVolume", + "MinX", + "MaxX", + "MinY", + "MaxY", + "MinZ", + "MaxZ", + "Extent", + "EulerNumber", + "EquivalentDiameter", + "SurfaceArea", + ] + + +def test_compute_requires_both_loaders() -> None: + """Partial invocation should fail with a clear contract error.""" + with pytest.raises(ZedProfilerError): + areasizeshape.compute(image_set_loader=DummyImageSetLoader()) + + with pytest.raises(ZedProfilerError): + areasizeshape.compute(object_loader=DummyObjectLoader()) + + +def test_compute_delegates_when_loaders_provided( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Compute should execute delegated measurement path with both loaders.""" + sentinel = {"object_id": [], "Volume": []} + + def _fake_measure( + image_set_loader: DummyImageSetLoader, + object_loader: DummyObjectLoader, + ) -> dict[str, list[float]]: + assert isinstance(image_set_loader, DummyImageSetLoader) + assert isinstance(object_loader, DummyObjectLoader) + return sentinel + + monkeypatch.setattr(areasizeshape, "measure_3D_area_size_shape", _fake_measure) + + result = areasizeshape.compute( + image_set_loader=DummyImageSetLoader(), + object_loader=DummyObjectLoader(), + ) + + assert result is sentinel + + +def test_empty_feature_result_schema() -> None: + """_empty_feature_result should return deterministic schema.""" + result = areasizeshape._empty_feature_result() + + expected_keys = { + "object_id", + "Volume", + "CenterX", + "CenterY", + "CenterZ", + "BboxVolume", + "MinX", + "MaxX", + "MinY", + "MaxY", + "MinZ", + "MaxZ", + "Extent", + "EulerNumber", + "EquivalentDiameter", + "SurfaceArea", + } + + assert set(result.keys()) == expected_keys + + for value in result.values(): + assert isinstance(value, list) + assert len(value) == 0 + + +def test_get_skimage_measure_import() -> None: + """Test that _get_skimage_measure successfully imports skimage.measure.""" + try: + measure = areasizeshape._get_skimage_measure() + # If scikit-image is available, check that it has expected functions + assert hasattr(measure, "marching_cubes") + assert hasattr(measure, "mesh_surface_area") + assert hasattr(measure, "regionprops") + except ZedProfilerError: + # If scikit-image is not available, that's also OK for this test + pytest.skip("scikit-image not available") + + +def test_get_skimage_measure_missing_raises_error( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Test that missing scikit-image raises appropriate error.""" + + def mock_import_module(name: str) -> object: + raise ModuleNotFoundError(f"No module named '{name}'") + + monkeypatch.setattr(areasizeshape, "import_module", mock_import_module) + + with pytest.raises(ZedProfilerError, match="scikit-image"): + areasizeshape._get_skimage_measure() + + +def test_calculate_surface_area_with_simple_data( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Test calculate_surface_area with mocked scikit-image.""" + # Create a simple 3D binary array with a small sphere-like region + label_object = np.zeros((7, 7, 7), dtype=np.uint8) + # Create a small ROI with gradient values for marching cubes + label_object[2:5, 2:5, 2:5] = np.array( + [ + [[0.0, 0.0, 0.0], [0.0, 0.5, 0.0], [0.0, 0.0, 0.0]], + [[0.0, 0.5, 0.0], [0.5, 1.0, 0.5], [0.0, 0.5, 0.0]], + [[0.0, 0.0, 0.0], [0.0, 0.5, 0.0], [0.0, 0.0, 0.0]], + ] + ) + + # Mock props for bounding box + props = { + "bbox-0": np.array([2]), + "bbox-1": np.array([2]), + "bbox-2": np.array([2]), + "bbox-3": np.array([5]), + "bbox-4": np.array([5]), + "bbox-5": np.array([5]), + } + + spacing = (1.0, 1.0, 1.0) + + try: + result = areasizeshape.calculate_surface_area(label_object, props, spacing) + # Result should be a float (surface area) + assert isinstance(result, (float, np.floating)) + assert result >= 0 + except ZedProfilerError: + # If scikit-image is not available, skip + pytest.skip("scikit-image not available") + + +def test_measure_3d_area_size_shape_returns_dict( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Test that measure_3D_area_size_shape returns correct structure.""" + + # Mock the loaders + def mock_import_module(name: str) -> object: + raise ModuleNotFoundError("scikit-image not available for test") + + monkeypatch.setattr(areasizeshape, "import_module", mock_import_module) + + # This should raise because _get_skimage_measure will fail + with pytest.raises(ZedProfilerError): + areasizeshape.measure_3D_area_size_shape( + DummyImageSetLoader(), + DummyObjectLoader(), + ) + + +def test_measure_3d_area_size_shape_with_real_data() -> None: + """Test measure_3D_area_size_shape with real scikit-image data.""" + try: + # Create a realistic 3D label image with two objects + label_image = np.zeros((10, 10, 10), dtype=np.int32) + # Object 1: a small cube + label_image[1:4, 1:4, 1:4] = 1 + # Object 2: another small cube + label_image[6:9, 6:9, 6:9] = 2 + + # Create real loaders + class RealImageSetLoader: + anisotropy_spacing = (1.0, 1.0, 1.0) + + class RealObjectLoader: + def __init__(self, label_image: np.ndarray) -> None: + self.label_image = label_image + self.object_ids = [1, 2] + + result = areasizeshape.measure_3D_area_size_shape( + RealImageSetLoader(), + RealObjectLoader(label_image), + ) + + # Verify structure + assert isinstance(result, dict) + + # Check all expected keys are present + expected_keys = { + "object_id", + "Volume", + "CenterX", + "CenterY", + "CenterZ", + "BboxVolume", + "MinX", + "MaxX", + "MinY", + "MaxY", + "MinZ", + "MaxZ", + "Extent", + "EulerNumber", + "EquivalentDiameter", + "SurfaceArea", + } + assert set(result.keys()) == expected_keys + + # Check that we have features for both objects + assert len(result["object_id"]) == NUM_TEST_OBJECTS + assert result["object_id"] == [1, 2] + # Verify all lists have same length + list_lengths = {k: len(v) for k, v in result.items()} + assert len(set(list_lengths.values())) == 1, "All lists should have same length" + + # Check Volume values are reasonable (23 voxels per 3x3x3 cube) + assert result["Volume"][0] > 0 + assert result["Volume"][1] > 0 + + # Check that center coordinates are within expected ranges + assert COORD_LOWER_BOUND <= result["CenterX"][0] <= COORD_UPPER_BOUND + assert COORD_LOWER_BOUND <= result["CenterY"][0] <= COORD_UPPER_BOUND + assert COORD_LOWER_BOUND <= result["CenterZ"][0] <= COORD_UPPER_BOUND + + # Check that extent values are between 0 and 1 + assert EXTENT_LOWER_BOUND <= result["Extent"][0] <= EXTENT_UPPER_BOUND + assert EXTENT_LOWER_BOUND <= result["Extent"][1] <= EXTENT_UPPER_BOUND + + except ZedProfilerError as e: + if "scikit-image" in str(e): + pytest.skip("scikit-image not available") + raise + + +def test_measure_3d_area_size_shape_empty_objects() -> None: + """Test measure_3D_area_size_shape with empty object list.""" + try: + # Create an empty label image + label_image = np.zeros((10, 10, 10), dtype=np.int32) + + class RealImageSetLoader: + anisotropy_spacing = (1.0, 1.0, 1.0) + + class RealObjectLoader: + def __init__(self, label_image: np.ndarray) -> None: + self.label_image = label_image + self.object_ids = [] # No objects + + result = areasizeshape.measure_3D_area_size_shape( + RealImageSetLoader(), + RealObjectLoader(label_image), + ) + + # Should return empty but valid structure + assert isinstance(result, dict) + for key, values in result.items(): + assert isinstance(values, list) + assert len(values) == 0 + + except ZedProfilerError as e: + if "scikit-image" in str(e): + pytest.skip("scikit-image not available") + raise + + +def test_measure_3d_area_size_shape_with_anisotropic_spacing() -> None: + """Test measure_3D_area_size_shape with anisotropic (non-uniform) spacing.""" + try: + # Create a label image + label_image = np.zeros((10, 10, 10), dtype=np.int32) + label_image[2:8, 2:8, 2:8] = 1 + + class AnisotropicImageSetLoader: + # Simulate higher resolution in Z axis + anisotropy_spacing = (0.5, 1.0, 1.0) + + class RealObjectLoader: + def __init__(self, label_image: np.ndarray) -> None: + self.label_image = label_image + self.object_ids = [1] + + result = areasizeshape.measure_3D_area_size_shape( + AnisotropicImageSetLoader(), + RealObjectLoader(label_image), + ) + + # Should handle anisotropic spacing correctly + assert len(result["object_id"]) == 1 + assert result["object_id"][0] == 1 + + except ZedProfilerError as e: + if "scikit-image" in str(e): + pytest.skip("scikit-image not available") + raise diff --git a/tests/featurization/test_featurization_modules.py b/tests/featurization/test_featurization_modules.py new file mode 100644 index 0000000..7a741d2 --- /dev/null +++ b/tests/featurization/test_featurization_modules.py @@ -0,0 +1,76 @@ +"""Tests for featurization modules.""" + +from __future__ import annotations + +import re + +import pytest + +from zedprofiler.exceptions import ZedProfilerError +from zedprofiler.featurization import ( + colocalization, + granularity, + intensity, + neighbors, + texture, +) + + +class TestColocationizationModule: + """Tests for colocalization featurization module.""" + + def test_compute_raises_not_implemented(self) -> None: + """Test that colocalization.compute raises ZedProfilerError.""" + with pytest.raises( + ZedProfilerError, + match=re.escape("colocalization.compute is not implemented yet"), + ): + colocalization.compute() + + +class TestGranularityModule: + """Tests for granularity featurization module.""" + + def test_compute_raises_not_implemented(self) -> None: + """Test that granularity.compute raises ZedProfilerError.""" + with pytest.raises( + ZedProfilerError, + match=re.escape("granularity.compute is not implemented yet"), + ): + granularity.compute() + + +class TestIntensityModule: + """Tests for intensity featurization module.""" + + def test_compute_raises_not_implemented(self) -> None: + """Test that intensity.compute raises ZedProfilerError.""" + with pytest.raises( + ZedProfilerError, + match=re.escape("intensity.compute is not implemented yet"), + ): + intensity.compute() + + +class TestNeighborsModule: + """Tests for neighbors featurization module.""" + + def test_compute_raises_not_implemented(self) -> None: + """Test that neighbors.compute raises ZedProfilerError.""" + with pytest.raises( + ZedProfilerError, + match=re.escape("neighbors.compute is not implemented yet"), + ): + neighbors.compute() + + +class TestTextureModule: + """Tests for texture featurization module.""" + + def test_compute_raises_not_implemented(self) -> None: + """Test that texture.compute raises ZedProfilerError.""" + with pytest.raises( + ZedProfilerError, + match=re.escape("texture.compute is not implemented yet"), + ): + texture.compute() diff --git a/uv.lock b/uv.lock index e5ad51b..29d591e 100644 --- a/uv.lock +++ b/uv.lock @@ -32,15 +32,14 @@ wheels = [ [[package]] name = "anyio" -version = "4.9.0" +version = "4.13.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "idna" }, - { name = "sniffio" }, ] -sdist = { url = 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