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578324d cc028f9 578324d cc028f9 578324d cc028f9 578324d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 | 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()
|