Tests for HDF5 load_manual

Author: hexane360

phaser/hooks/__init__.py

@@ -59,6 +59,8 @@ class LoadManualProps(Dataclass, kw_only=True):
     """Detector ADU, representing the single-particle signal. Used to scale patterns."""
 
     det_flips: t.Optional[t.Tuple[bool, bool, bool]] = None
+    fftshifted: bool = False
+    """Whether patterns are fftshifted (zero-frequency in corner of array)"""
 
 class RawDataHook(Hook[None, RawData]):
     known = {

phaser/hooks/io/manual.py

@@ -40,7 +40,7 @@ def load_manual(args: None, props: LoadManualProps) -> RawData:
         logger.info("Loading as TIFF...")
         import tifffile
         patterns = numpy.asarray(tifffile.imread(path))
-    elif ext in ('.h5', '.hdf5'):
+    elif ext in ('.h5', '.hdf5', '.emd'):
         logger.info("Loading as HDF5...")
         patterns = _load_hdf5(path, props.key, logger)
     elif ext in ('.mat',):
@@ -100,9 +100,13 @@ def load_manual(args: None, props: LoadManualProps) -> RawData:
 
     mask = numpy.ones_like(patterns, shape=patterns.shape[-2:])
 
+    if not props.fftshifted:
+        patterns = numpy.fft.ifftshift(patterns, axes=(-1, -2))
+        mask = numpy.fft.ifftshift(mask, axes=(-1, -2))
+
     return {
-        'patterns': numpy.fft.ifftshift(patterns, axes=(-1, -2)),
-        'mask': numpy.fft.ifftshift(mask, axes=(-1, -2)),
+        'patterns': patterns,
+        'mask': mask,
         'sampling': sampling,
         'wavelength': wavelength,
         'probe_hook': None,
@@ -118,8 +122,8 @@ def _normalize_key(key: str) -> t.Tuple[str, ...]:
 
 
 _HDF5_KNOWN_KEYS: t.List[t.Tuple[str, ...]] = [
-    ('dp,',),
-    ('data,',),
+    ('dp',),
+    ('data',),
 ]
 
 

tests/input_files/dp.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3c878e2bcf0e6875225880bf133ac812714abfbf0fcb7795561c7989355d330
+size 264192

tests/input_files/dp_customkey.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca1d16aad07e72c16826ebed48c527ef99c4bdfa95c02642b29ea5a491a69ab3
+size 266640

tests/test_load.py

@@ -71,6 +71,59 @@ def test_load_manual_empad_v1(caplog, expected_raw_data: RawData):
     assert_raw_data_matches(raw_data, expected_raw_data, (4,))
 
 
+def test_load_manual_h5py(caplog, expected_raw_data: RawData):
+    caplog.set_level(logging.INFO)
+    get_backend_module("numpy")
+
+    hook = pane.from_data(
+        {
+            "type": "manual",
+            "wavelength": 0.0251,
+            "path": INPUT_FILES_PATH / "dp.h5",
+            "diff_step": 0.4,
+            "fftshifted": True,
+        },  # type: ignore
+        RawDataHook,
+    )
+    raw_data = hook(None)
+
+    assert caplog.record_tuples == [
+        ("phaser.hooks.io.manual", logging.INFO, "Loading as HDF5..."),
+        ("phaser.hooks.io.manual", logging.INFO, "Found patterns at key 'dp' (inferred) in HDF5 file."),
+        ("phaser.hooks.io.manual", logging.INFO, "Applying detector flips: [0, 0, 0] [y, x, transpose]"),
+        ("phaser.hooks.io.manual", logging.WARNING, "ADU not supplied for experimental dataset. This is not recommended."),
+    ]
+
+    assert_raw_data_matches(raw_data, expected_raw_data, (2, 2))
+
+
+def test_load_manual_h5py_customkey(caplog, expected_raw_data: RawData):
+    caplog.set_level(logging.INFO)
+    get_backend_module("numpy")
+
+    hook = pane.from_data(
+        {
+            "type": "manual",
+            "wavelength": 0.0251,
+            "path": INPUT_FILES_PATH / "dp_customkey.h5",
+            "key": "a/b/c/d",
+            "diff_step": 0.4,
+            "fftshifted": True,
+        },  # type: ignore
+        RawDataHook,
+    )
+    raw_data = hook(None)
+
+    assert caplog.record_tuples == [
+        ("phaser.hooks.io.manual", logging.INFO, "Loading as HDF5..."),
+        ("phaser.hooks.io.manual", logging.INFO, "Loaded patterns from key 'a/b/c/d' in HDF5 file."),
+        ("phaser.hooks.io.manual", logging.INFO, "Applying detector flips: [0, 0, 0] [y, x, transpose]"),
+        ("phaser.hooks.io.manual", logging.WARNING, "ADU not supplied for experimental dataset. This is not recommended."),
+    ]
+
+    assert_raw_data_matches(raw_data, expected_raw_data, (2, 2))
+
+
 def test_load_manual_tiff(caplog, expected_raw_data: RawData):
     caplog.set_level(logging.INFO)
     get_backend_module("numpy")