docs/changes/newsfragments/252.change

@@ -0,0 +1 @@
+Add ``native_t1w`` parameter to :class:`.DataladAOMICID1000`, :class:`.DataladAOMICPIOP1`, :class:`.DataladAOMICPIOP2`, enabling fetching of T1w data in subject-native space by `Synchon Mandal`_

docs/changes/newsfragments/252.feature

@@ -0,0 +1 @@
+Add support for subject-native space by `Synchon Mandal`_ and `Fede Raimondo`_

junifer/datagrabber/aomic/id1000.py

@@ -28,6 +28,8 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
            "probseg_WM", "DWI"} or a list of the options, optional
         AOMIC data types. If None, all available data types are selected.
         (default None).
+    native_t1w : bool, optional
+        Whether to use T1w in native space (default False).
 
     """
 
@@ -35,6 +37,7 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
         self,
         datadir: Union[str, Path, None] = None,
         types: Union[str, List[str], None] = None,
+        native_t1w: bool = False,
     ) -> None:
         # The patterns
         patterns = {
@@ -84,6 +87,27 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
+        # Use native T1w assets
+        self.native_t1w = False
+        if native_t1w:
+            self.native_t1w = True
+            patterns.update(
+                {
+                    "T1w": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-preproc_T1w.nii.gz"
+                    ),
+                    "T1w_mask": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-brain_mask.nii.gz"
+                    ),
+                    "Warp": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_from-MNI152NLin2009cAsym_to-T1w_"
+                        "mode-image_xfm.h5"
+                    ),
+                }
+            )
         # Set default types
         if types is None:
             types = list(patterns.keys())
@@ -126,5 +150,8 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
         if out.get("T1w"):
             out["T1w"]["mask_item"] = "T1w_mask"
             # Add space information
-            out["T1w"].update({"space": "native"})
+            if self.native_t1w:
+                out["T1w"].update({"space": "native"})
+            else:
+                out["T1w"].update({"space": "MNI152NLin2009cAsym"})
         return out

junifer/datagrabber/aomic/piop1.py

@@ -34,6 +34,8 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
             "gstroop", "workingmemory"} or list of the options, optional
         AOMIC PIOP1 task sessions. If None, all available task sessions are
         selected (default None).
+    native_t1w : bool, optional
+        Whether to use T1w in native space (default False).
 
     """
 
@@ -42,6 +44,7 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         datadir: Union[str, Path, None] = None,
         types: Union[str, List[str], None] = None,
         tasks: Union[str, List[str], None] = None,
+        native_t1w: bool = False,
     ) -> None:
         # Declare all tasks
         all_tasks = [
@@ -114,6 +117,27 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
+        # Use native T1w assets
+        self.native_t1w = False
+        if native_t1w:
+            self.native_t1w = True
+            patterns.update(
+                {
+                    "T1w": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-preproc_T1w.nii.gz"
+                    ),
+                    "T1w_mask": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-brain_mask.nii.gz"
+                    ),
+                    "Warp": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_from-MNI152NLin2009cAsym_to-T1w_"
+                        "mode-image_xfm.h5"
+                    ),
+                }
+            )
         # Set default types
         if types is None:
             types = list(patterns.keys())
@@ -171,7 +195,10 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         if out.get("T1w"):
             out["T1w"]["mask_item"] = "T1w_mask"
             # Add space information
-            out["T1w"].update({"space": "native"})
+            if self.native_t1w:
+                out["T1w"].update({"space": "native"})
+            else:
+                out["T1w"].update({"space": "MNI152NLin2009cAsym"})
         return out
 
     def get_elements(self) -> List:

junifer/datagrabber/aomic/piop2.py

@@ -34,6 +34,8 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
             or list of the options, optional
         AOMIC PIOP2 task sessions. If None, all available task sessions are
         selected (default None).
+    native_t1w : bool, optional
+        Whether to use T1w in native space (default False).
 
     """
 
@@ -42,6 +44,7 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         datadir: Union[str, Path, None] = None,
         types: Union[str, List[str], None] = None,
         tasks: Union[str, List[str], None] = None,
+        native_t1w: bool = False,
     ) -> None:
         # Declare all tasks
         all_tasks = [
@@ -111,6 +114,27 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
+        # Use native T1w assets
+        self.native_t1w = False
+        if native_t1w:
+            self.native_t1w = True
+            patterns.update(
+                {
+                    "T1w": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-preproc_T1w.nii.gz"
+                    ),
+                    "T1w_mask": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_desc-brain_mask.nii.gz"
+                    ),
+                    "Warp": (
+                        "derivatives/fmriprep/sub-{subject}/anat/"
+                        "sub-{subject}_from-MNI152NLin2009cAsym_to-T1w_"
+                        "mode-image_xfm.h5"
+                    ),
+                }
+            )
         # Set default types
         if types is None:
             types = list(patterns.keys())
@@ -171,5 +195,8 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         if out.get("T1w"):
             out["T1w"]["mask_item"] = "T1w_mask"
             # Add space information
-            out["T1w"].update({"space": "native"})
+            if self.native_t1w:
+                out["T1w"].update({"space": "native"})
+            else:
+                out["T1w"].update({"space": "MNI152NLin2009cAsym"})
         return out

junifer/datagrabber/hcp1200/hcp1200.py

@@ -98,7 +98,7 @@ class HCP1200(PatternDataGrabber):
                 )
         suffix = "_hp2000_clean" if ica_fix else ""
         # The types of data
-        types = ["BOLD"]
+        types = ["BOLD", "T1w", "Warp"]
         # The patterns
         patterns = {
             "BOLD": (
@@ -106,7 +106,9 @@ class HCP1200(PatternDataGrabber):
                 "{task}_{phase_encoding}/"
                 "{task}_{phase_encoding}"
                 f"{suffix}.nii.gz"
-            )
+            ),
+            "T1w": "{subject}/T1w/T1w_acpc_dc_restore.nii.gz",
+            "Warp": "{subject}/MNINonLinear/xfms/standard2acpc_dc.nii.gz",
         }
         # The replacements
         replacements = ["subject", "task", "phase_encoding"]
@@ -147,6 +149,12 @@ class HCP1200(PatternDataGrabber):
         out = super().get_item(
             subject=subject, task=new_task, phase_encoding=phase_encoding
         )
+        # Add space for BOLD data type
+        if "BOLD" in out:
+            out["BOLD"].update({"space": "MNI152NLin6Asym"})
+        # Add space for T1w data type
+        if "T1w" in out:
+            out["T1w"].update({"space": "native"})
         return out
 
     def get_elements(self) -> List:

junifer/datareader/default.py

@@ -104,6 +104,10 @@ class DefaultDataReader(PipelineStepMixin, UpdateMetaMixin):
             params = {}
         # For each type of data, try to read it
         for type_ in input.keys():
+            # Skip Warp data type
+            if type_ == "Warp":
+                continue
+
             # Check for malformed datagrabber specification
             if "path" not in input[type_]:
                 warn_with_log(

tools/create_hcp1200_example_dataset.py

@@ -4,8 +4,8 @@
 # License: AGPL
 
 from itertools import product
-from tempfile import TemporaryDirectory
 from pathlib import Path
+from tempfile import TemporaryDirectory
 
 import datalad.api as dl
 
@@ -15,7 +15,6 @@ DST = "git@gin.g-node.org:/juaml/datalad-example-hcp1200.git"
 
 
 if __name__ == "__main__":
-
     with TemporaryDirectory() as tmpdir:
         # Convert str to Path
         tmpdir_path = Path(tmpdir)
@@ -29,7 +28,30 @@ if __name__ == "__main__":
             # Create subject directory
             subdir.mkdir()
 
-            for (task, phase_encoding) in product(
+            # T1w data
+            # Set subject data directory
+            sub_t1w_datadir = subdir / "T1w"
+            # Create subject data directory
+            sub_t1w_datadir.mkdir(parents=True)
+            # Set subject data file
+            sub_t1w_datafile = sub_t1w_datadir / "T1w_acpc_dc_restore.nii.gz"
+            # Write subject data file
+            with open(sub_t1w_datafile, "w") as f:
+                f.write("placeholder")
+
+            # Warp data
+            # Set subject data directory
+            sub_warp_datadir = subdir / "MNINonLinear" / "xfms"
+            # Create subject data directory
+            sub_warp_datadir.mkdir(parents=True)
+            # Set subject data file
+            sub_warp_datafile = sub_warp_datadir / "standard2acpc_dc.nii.gz"
+            # Write subject data file
+            with open(sub_warp_datafile, "w") as f:
+                f.write("placeholder")
+
+            # BOLD data
+            for task, phase_encoding in product(
                 [
                     "REST1",
                     "REST2",
@@ -49,32 +71,31 @@ if __name__ == "__main__":
                 else:
                     new_task = f"tfMRI_{task}"
                 # Set subject data directory
-                sub_datadir = (
+                sub_bold_datadir = (
                     subdir
                     / "MNINonLinear"
                     / "Results"
                     / f"{new_task}_{phase_encoding}"
                 )
                 # Create subject data directory
-                sub_datadir.mkdir(parents=True)
+                sub_bold_datadir.mkdir(parents=True)
 
                 # Set subject data file
-                sub_datafile = (
-                    sub_datadir
-                    / f"{new_task}_{phase_encoding}.nii.gz"
+                sub_bold_datafile = (
+                    sub_bold_datadir / f"{new_task}_{phase_encoding}.nii.gz"
                 )
                 # Create subject data file
-                with open(sub_datafile, "w") as f:
+                with open(sub_bold_datafile, "w") as f:
                     f.write("placeholder")
 
                 if "REST" in task:
                     # Set subject data file with ICA+FIX
-                    sub_datafile = (
-                        sub_datadir
+                    sub_bold_datafile = (
+                        sub_bold_datadir
                         / f"{new_task}_{phase_encoding}_hp2000_clean.nii.gz"
                     )
                     # Create subject data file with ICA+FIX
-                    with open(sub_datafile, "w") as f:
+                    with open(sub_bold_datafile, "w") as f:
                         f.write("placeholder")
 
         # Save datalad dataset