| from __future__ import annotations |
|
|
| import tempfile |
| import unittest |
| import zipfile |
| from pathlib import Path |
| from types import SimpleNamespace |
| from unittest.mock import patch |
|
|
| import nibabel as nib |
| import numpy as np |
|
|
| from scripts.luna16_collect_upload import ( |
| convert_mhd_fields_to_nifti, |
| create_manifest_candidate, |
| mhd_and_raw_member, |
| ) |
| from scripts.hf_commit import create_commit_with_rate_limit_retry |
| from huggingface_hub.errors import HfHubHTTPError |
| from scripts.storage_guard import StorageBudget, extract_member_bounded |
| from scripts.tcia_collect_upload import ( |
| create_manifest_candidate as create_tcia_manifest_candidate, |
| dicom_to_nifti, |
| ) |
|
|
|
|
| class ConversionTests(unittest.TestCase): |
| def test_tcia_manifest_candidate_appends_atomic_batch(self) -> None: |
| with tempfile.TemporaryDirectory() as tmp: |
| path = Path(tmp) / "manifest.jsonl" |
| existing = [{"folder": "case-1"}] |
| added = [{"folder": "case-2"}, {"folder": "case-3"}] |
| candidate = create_tcia_manifest_candidate(path, existing, added) |
| try: |
| import json |
|
|
| rows = [json.loads(line) for line in candidate.read_text().splitlines()] |
| finally: |
| candidate.unlink(missing_ok=True) |
| self.assertEqual(rows, existing + added) |
|
|
| def test_luna_manifest_candidate_appends_atomic_batch(self) -> None: |
| with tempfile.TemporaryDirectory() as tmp: |
| path = Path(tmp) / "manifest.jsonl" |
| existing = [{"folder": "case-1"}] |
| added = [{"folder": "case-2"}, {"folder": "case-3"}] |
| candidate = create_manifest_candidate(path, existing, added) |
| try: |
| import json |
|
|
| rows = [json.loads(line) for line in candidate.read_text().splitlines()] |
| finally: |
| candidate.unlink(missing_ok=True) |
| self.assertEqual(rows, existing + added) |
|
|
| def test_luna_commit_retries_only_rate_limit(self) -> None: |
| class FakeApi: |
| calls = 0 |
|
|
| def create_commit(self, **kwargs): |
| self.calls += 1 |
| if self.calls == 1: |
| response = SimpleNamespace( |
| status_code=429, |
| headers={"retry-after": "2"}, |
| request=SimpleNamespace(), |
| ) |
| raise HfHubHTTPError("rate limited", response=response) |
| return kwargs["commit_message"] |
|
|
| sleeps: list[float] = [] |
| api = FakeApi() |
| result = create_commit_with_rate_limit_retry( |
| api, |
| max_wait_seconds=10, |
| sleep_interval_seconds=1, |
| sleep_fn=sleeps.append, |
| commit_message="batched", |
| ) |
| self.assertEqual(result, "batched") |
| self.assertEqual(api.calls, 2) |
| self.assertEqual(sleeps, [1, 1]) |
|
|
| def test_luna_archive_extracts_only_selected_raw_member(self) -> None: |
| mhd = "\n".join( |
| [ |
| "DimSize = 2 2 2", |
| "ElementSpacing = 1 1 1", |
| "ElementType = MET_SHORT", |
| "ElementDataFile = scan.raw", |
| ] |
| ) |
| raw = np.arange(8, dtype="<i2").tobytes() |
| with tempfile.TemporaryDirectory() as tmp: |
| root = Path(tmp) |
| archive = root / "subset.zip" |
| with zipfile.ZipFile(archive, "w") as zf: |
| zf.writestr("subset/scan.mhd", mhd) |
| zf.writestr("subset/scan.raw", raw) |
|
|
| budget = StorageBudget(root, max_local_bytes=1024**2, min_free_bytes=0) |
| with zipfile.ZipFile(archive) as zf: |
| fields, raw_member = mhd_and_raw_member(zf, "subset/scan.mhd") |
| destination = root / "selected.raw" |
| extract_member_bounded(zf, raw_member, destination, budget) |
|
|
| self.assertEqual(fields["ElementDataFile"], "scan.raw") |
| self.assertEqual(raw_member, "subset/scan.raw") |
| self.assertEqual(destination.read_bytes(), raw) |
| self.assertFalse((root / "subset/scan.mhd").exists()) |
|
|
| def test_luna_mhd_shape_values_and_affine(self) -> None: |
| fields = { |
| "DimSize": "2 2 2", |
| "ElementSpacing": "1 2 3", |
| "Offset": "10 20 30", |
| "TransformMatrix": "1 0 0 0 1 0 0 0 1", |
| "ElementType": "MET_SHORT", |
| "BinaryDataByteOrderMSB": "False", |
| } |
| with tempfile.TemporaryDirectory() as tmp: |
| root = Path(tmp) |
| raw_path = root / "scan.raw" |
| out_path = root / "ct.nii.gz" |
| np.arange(8, dtype="<i2").tofile(raw_path) |
|
|
| metadata = convert_mhd_fields_to_nifti(fields, raw_path, out_path) |
| image = nib.load(out_path) |
| data = np.asanyarray(image.dataobj) |
|
|
| self.assertEqual(metadata["shape"], [2, 2, 2]) |
| np.testing.assert_array_equal(data, np.arange(8, dtype=np.int16).reshape(2, 2, 2).transpose(2, 1, 0)) |
| np.testing.assert_allclose( |
| image.affine, |
| np.array( |
| [ |
| [-1, 0, 0, -10], |
| [0, -2, 0, -20], |
| [0, 0, 3, 30], |
| [0, 0, 0, 1], |
| ], |
| dtype=float, |
| ), |
| ) |
|
|
| def test_tcia_origin_uses_first_sorted_slice(self) -> None: |
| def make_slice(z: float, value: int) -> SimpleNamespace: |
| return SimpleNamespace( |
| ImageOrientationPatient=[1, 0, 0, 0, 1, 0], |
| ImagePositionPatient=[0, 0, z], |
| PixelSpacing=[2, 3], |
| SliceThickness=10, |
| RescaleSlope=1, |
| RescaleIntercept=0, |
| pixel_array=np.full((2, 3), value, dtype=np.int16), |
| ) |
|
|
| unsorted_slices = [make_slice(10, 10), make_slice(0, 0)] |
| with tempfile.TemporaryDirectory() as tmp: |
| out_path = Path(tmp) / "ct.nii.gz" |
| with patch( |
| "scripts.tcia_collect_upload.read_dicom_slices", |
| return_value=unsorted_slices, |
| ): |
| dicom_to_nifti([], out_path) |
|
|
| image = nib.load(out_path) |
| data = np.asanyarray(image.dataobj) |
| self.assertEqual(data.shape, (3, 2, 2)) |
| np.testing.assert_array_equal(data[:, :, 0], 0) |
| np.testing.assert_array_equal(data[:, :, 1], 10) |
| self.assertEqual(float(image.affine[2, 3]), 0.0) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
