Adding extra nifti test samples

tests/integration/converters/test_nifti.py

@@ -7,35 +7,43 @@
 from tiledb.bioimg.converters.nifti import NiftiConverter
 
 
-def compare_nifti_images(file1, file2):
+def compare_nifti_images(file1, file2, scaled_test):
     img1 = nib.load(file1)
     img2 = nib.load(file2)
 
-    # Compare the headers (metadata)
-    if img1.header != img2.header:
-        return False
-
     # Compare the affine matrices (spatial information)
-    if not np.array_equal(img1.affine, img2.affine):
-        return False
+    assert np.array_equal(img1.affine, img2.affine)
 
     # Compare the image data (voxel data)
-    data1 = img1.get_fdata()
-    data2 = img2.get_fdata()
-    if not np.array_equal(data1, data2):
-        return False
-    return True
+    data1 = np.array(img1.dataobj, dtype=img1.get_data_dtype())
+    data2 = np.array(img2.dataobj, dtype=img2.get_data_dtype())
+
+    assert np.array_equal(data1, data2)
+
+    # Compare the image data scaled (voxel data)
+    if scaled_test:
+        data_sc = img1.get_fdata()
+        data_sc_2 = img2.get_fdata()
+
+        assert np.array_equal(data_sc, data_sc_2)
 
 
 @pytest.mark.parametrize(
-    "filename", ["nifti/example4d.nii", "nifti/functional.nii", "nifti/standard.nii"]
+    "filename",
+    [
+        "nifti/example4d.nii",
+        "nifti/functional.nii",
+        "nifti/standard.nii",
+        "nifti/visiblehuman.nii",
+        "nifti/anatomical.nii",
+    ],
 )
 @pytest.mark.parametrize("preserve_axes", [False, True])
 @pytest.mark.parametrize("chunked", [False])
 @pytest.mark.parametrize(
     "compressor, lossless",
     [
-        (tiledb.ZstdFilter(level=0), True),
+        (tiledb.ZstdFilter(level=0), False),
         # WEBP is not supported for Grayscale images
     ],
 )
@@ -57,4 +65,9 @@ def test_nifti_converter_roundtrip(
     )
     # Store it back to PNG
     NiftiConverter.from_tiledb(tiledb_path, output_path)
-    compare_nifti_images(input_path, output_path)
+    # The dtype of this image is complex and nibabel breaks originally
+    compare_nifti_images(
+        input_path,
+        output_path,
+        scaled_test=False if filename == "nifti/visiblehuman.nii" else True,
+    )

tiledb/bioimg/converters/nifti.py

@@ -29,6 +29,14 @@
 from .base import ImageConverterMixin
 
 
+# Function to find and return the third value based on the first value
+def get_dtype_from_code(dtype_code: int) -> Optional[np.dtype]:
+    for item in _dtdefs:
+        if item[0] == dtype_code:  # Check if the first value matches the input code
+            return item[2]  # Return the third value (dtype)
+    return None  # Return None if the code is not found
+
+
 class NiftiReader:
     _logger: logging.Logger
 
@@ -83,7 +91,12 @@ def logger(self) -> Optional[logging.Logger]:
 
     @property
     def group_metadata(self) -> Dict[str, Any]:
-        writer_kwargs = dict(metadata=self._metadata, binaryblock=self._binary_header)
+        writer_kwargs = dict(
+            metadata=self._metadata,
+            binaryblock=self._binary_header,
+            slope=self._nib_image.dataobj.slope,
+            inter=self._nib_image.dataobj.inter,
+        )
         self._logger.debug(f"Group metadata: {writer_kwargs}")
         return {"json_write_kwargs": json.dumps(writer_kwargs)}
 
@@ -173,7 +186,7 @@ def level_count(self) -> int:
     def level_dtype(self, level: int = 0) -> np.dtype:
         header_dict = self.nifti1_hdr_2_dict()
 
-        dtype = self.get_dtype_from_code(header_dict["datatype"])
+        dtype = get_dtype_from_code(header_dict["datatype"])
         if dtype == np.dtype([("R", "u1"), ("G", "u1"), ("B", "u1")]):
             dtype = np.uint8
         # TODO: Compare with the dtype of fields
@@ -218,8 +231,14 @@ def level_image(
         self._metadata["original_mode"] = self._mode
         raw_data_contiguous = np.ascontiguousarray(unscaled_img)
         numerical_data = np.frombuffer(raw_data_contiguous, dtype=self.level_dtype())
+        # Account endianness
+        numerical_data = numerical_data.view(
+            numerical_data.dtype.newbyteorder(self._nib_image.header.endianness)
+        )
         numerical_data = numerical_data.reshape(self.level_shape())
 
+        # Bug! data might have slope and inter and header not contain them.
+
         if tile is None:
             return numerical_data
         else:
@@ -256,13 +275,6 @@ def nifti1_hdr_2_dict(self) -> Dict[str, Any]:
             for field in structured_header_arr.dtype.names
         }
 
-    # Function to find and return the third value based on the first value
-    def get_dtype_from_code(self, dtype_code: int) -> np.dtype:
-        for item in _dtdefs:
-            if item[0] == dtype_code:  # Check if the first value matches the input code
-                return item[2]  # Return the third value (dtype)
-        return None  # Return None if the code is not foun
-
     @staticmethod
     def _serialize_header(header_dict: Mapping[str, Any]) -> Dict[str, Any]:
         serialized_header = {
@@ -335,6 +347,10 @@ def write_level_image(
         nib_image = self._writer(
             structured_arr, header=header, affine=header.get_best_affine()
         )
+
+        nib_image.header.set_slope_inter(
+            self._group_metadata["slope"], self._group_metadata["inter"]
+        )
         nib.save(nib_image, self._output_path)
 
     def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None: