Tests for fetch slice

src/hdf5_reader_service/tasks/slice.py

@@ -15,20 +15,16 @@ def fetch_slice(
         slices = tuple(
             map(lambda t: slice(*map(int, t.split(":"))), slice_info.split(","))
         )
-    else:
-        # Default to getting the whole dataset
-        # slices = ...
-        pass
 
     with h5py.File(path, "r", swmr=swmr, libver="latest") as f:
         if subpath in f:
             dataset = f[subpath]
             if isinstance(dataset, h5py.Dataset):
                 return dataset[slices]
             else:
-                raise Exception(
+                raise KeyError(
                     f"Expected {subpath} to be a dataset, \
                         it is acually a {type(dataset)}"
                 )
         else:
-            raise Exception(f"{path} does not contain {subpath}")
+            raise KeyError(f"{path} does not contain {subpath}")

tests/tasks/test_slice.py

@@ -0,0 +1,165 @@
+import sys
+import time
+from pathlib import Path
+from typing import Callable, Mapping
+
+import h5py as h5
+import numpy as np
+import pytest
+
+from hdf5_reader_service.tasks import fetch_slice
+
+TEST_CASES: Mapping[str, np.ndarray] = {
+    "0:1:1,0:1:1,0:1:1,0:10:1": np.array(
+        [[[[18, 19, 19, 20, 20, 21, 21, 22, 22, 23]]]], dtype=np.uint8
+    ),
+    "0:1:1,0:1:1,0:3:1,0:3:1": np.array(
+        [[[[18, 19, 19], [19, 19, 20], [19, 20, 20]]]], dtype=np.uint8
+    ),
+    "0:1:1,0:2:1,0:3:1,0:3:1": np.array(
+        [
+            [
+                [[18, 19, 19], [19, 19, 20], [19, 20, 20]],
+                [[8, 8, 9], [8, 9, 9], [9, 9, 9]],
+            ]
+        ],
+        dtype=np.uint8,
+    ),
+    "0:3:1,0:3:1,0:3:1,0:3:1": np.array(
+        [
+            [
+                [[18, 19, 19], [19, 19, 20], [19, 20, 20]],
+                [[8, 8, 9], [8, 9, 9], [9, 9, 9]],
+                [[25, 25, 26], [26, 26, 27], [26, 27, 28]],
+            ],
+            [
+                [[2, 2, 2], [2, 2, 2], [2, 2, 2]],
+                [[1, 1, 1], [1, 1, 1], [1, 1, 1]],
+                [[3, 3, 4], [4, 4, 4], [4, 4, 4]],
+            ],
+            [
+                [[6, 6, 6], [6, 6, 6], [6, 6, 7]],
+                [[7, 8, 8], [8, 8, 8], [8, 8, 8]],
+                [[28, 29, 29], [29, 30, 30], [30, 31, 31]],
+            ],
+        ],
+        dtype=np.uint8,
+    ),
+    "2:7:1,10:14:1,9:10:1,0:3:1": np.array(
+        [
+            [[[40, 41, 42]], [[40, 41, 42]], [[30, 31, 32]], [[32, 33, 34]]],
+            [[[41, 42, 43]], [[41, 42, 43]], [[37, 38, 39]], [[23, 23, 24]]],
+            [[[40, 41, 42]], [[41, 43, 44]], [[39, 40, 41]], [[34, 35, 36]]],
+            [[[41, 42, 43]], [[42, 43, 44]], [[31, 32, 32]], [[35, 36, 37]]],
+            [[[40, 41, 42]], [[41, 42, 44]], [[35, 36, 37]], [[23, 24, 24]]],
+        ],
+        dtype=np.uint8,
+    ),
+    "0:10:4,0:2:1,0:20:2,0:20:10": np.array(
+        [
+            [
+                [
+                    [18, 23],
+                    [19, 25],
+                    [21, 26],
+                    [22, 28],
+                    [24, 30],
+                    [25, 32],
+                    [26, 33],
+                    [28, 35],
+                    [29, 37],
+                    [31, 39],
+                ],
+                [
+                    [8, 10],
+                    [9, 11],
+                    [9, 12],
+                    [10, 13],
+                    [11, 13],
+                    [11, 14],
+                    [12, 15],
+                    [12, 16],
+                    [13, 17],
+                    [14, 18],
+                ],
+            ],
+            [
+                [
+                    [28, 36],
+                    [30, 39],
+                    [33, 41],
+                    [35, 44],
+                    [37, 47],
+                    [39, 49],
+                    [41, 52],
+                    [43, 55],
+                    [46, 58],
+                    [48, 61],
+                ],
+                [
+                    [29, 37],
+                    [31, 40],
+                    [33, 42],
+                    [35, 45],
+                    [38, 48],
+                    [40, 51],
+                    [42, 54],
+                    [44, 56],
+                    [47, 59],
+                    [49, 62],
+                ],
+            ],
+            [
+                [
+                    [28, 36],
+                    [30, 38],
+                    [32, 41],
+                    [34, 44],
+                    [36, 46],
+                    [39, 49],
+                    [41, 52],
+                    [43, 55],
+                    [45, 57],
+                    [48, 60],
+                ],
+                [
+                    [6, 8],
+                    [7, 8],
+                    [7, 9],
+                    [8, 10],
+                    [8, 10],
+                    [9, 11],
+                    [9, 12],
+                    [10, 12],
+                    [10, 13],
+                    [11, 14],
+                ],
+            ],
+        ],
+        dtype=np.uint8,
+    ),
+}
+
+
+@pytest.mark.parametrize("slice_info,expected", TEST_CASES.items())
+def test_fetch_slice(
+    test_data_path: Path,
+    slice_info: str,
+    expected: np.ndarray,
+) -> None:
+    np.set_printoptions(threshold=sys.maxsize)
+    data_slice = fetch_slice(
+        str(test_data_path), "/entry/DIFFRACTION/data", slice_info, True
+    )
+    print(data_slice.tolist())
+    np.testing.assert_array_equal(data_slice, expected)
+
+
+def test_fetch_slice_of_group(test_data_path: Path) -> None:
+    with pytest.raises(KeyError):
+        fetch_slice(str(test_data_path), "/entry", None, True)
+
+
+def test_fetch_slice_of_broken_link(test_data_path: Path) -> None:
+    with pytest.raises(KeyError):
+        fetch_slice(str(test_data_path), "/entry/DIFFRACTION/simx", None, True)