[ENH] Simplify imports for DWI pipelines (#1072)

clinica/pipelines/dwi_connectome/__init__.py

@@ -1 +1 @@
-from . import dwi_connectome_cli
+from . import cli

clinica/pipelines/dwi_connectome/dwi_connectome_cli.py → clinica/pipelines/dwi_connectome/cli.py

@@ -41,7 +41,7 @@ def cli(
 
     from clinica.utils.ux import print_end_pipeline
 
-    from .dwi_connectome_pipeline import DwiConnectome
+    from .pipeline import DwiConnectome
 
     parameters = {"n_tracks": n_tracks}
 

clinica/pipelines/dwi_connectome/dwi_connectome_pipeline.py → clinica/pipelines/dwi_connectome/pipeline.py

@@ -192,7 +192,7 @@ def _build_output_node(self):
         import nipype.interfaces.utility as nutil
         import nipype.pipeline.engine as npe
 
-        import clinica.pipelines.dwi_connectome.dwi_connectome_utils as utils
+        from .utils import get_containers
 
         join_node = npe.JoinNode(
             name="JoinOutputs",
@@ -212,7 +212,7 @@ def _build_output_node(self):
             ),
         )
         write_node.inputs.base_directory = str(self.caps_directory)
-        write_node.inputs.container = utils.get_containers(self.subjects, self.sessions)
+        write_node.inputs.container = get_containers(self.subjects, self.sessions)
         write_node.inputs.substitutions = [("trait_added", "")]
         write_node.inputs.parameterization = False
 
@@ -271,12 +271,19 @@ def _build_core_nodes(self):
             Tractography,
         )
 
-        import clinica.pipelines.dwi_connectome.dwi_connectome_utils as utils
         from clinica.utils.exceptions import ClinicaCAPSError
         from clinica.utils.mri_registration import (
             convert_flirt_transformation_to_mrtrix_transformation,
         )
 
+        from .utils import (
+            get_caps_filenames,
+            get_conversion_luts,
+            get_luts,
+            print_begin_pipeline,
+            print_end_pipeline,
+        )
+
         # Nodes
         # =====
         # B0 Extraction (only if space=b0)
@@ -328,8 +335,8 @@ def _build_core_nodes(self):
             iterfield=["in_file", "in_config", "in_lut", "out_file"],
             interface=mrtrix3.LabelConvert(),
         )
-        label_convert_node.inputs.in_config = utils.get_conversion_luts()
-        label_convert_node.inputs.in_lut = utils.get_luts()
+        label_convert_node.inputs.in_config = get_conversion_luts()
+        label_convert_node.inputs.in_lut = get_luts()
 
         # FSL flirt matrix to MRtrix matrix Conversion (only if space=b0)
         # --------------------------------------------
@@ -391,7 +398,7 @@ def _build_core_nodes(self):
         print_begin_message = npe.MapNode(
             interface=niu.Function(
                 input_names=["in_bids_or_caps_file"],
-                function=utils.print_begin_pipeline,
+                function=print_begin_pipeline,
             ),
             iterfield="in_bids_or_caps_file",
             name="WriteBeginMessage",
@@ -402,7 +409,7 @@ def _build_core_nodes(self):
         print_end_message = npe.MapNode(
             interface=niu.Function(
                 input_names=["in_bids_or_caps_file", "final_file"],
-                function=utils.print_end_pipeline,
+                function=print_end_pipeline,
             ),
             iterfield=["in_bids_or_caps_file"],
             name="WriteEndMessage",
@@ -415,7 +422,7 @@ def _build_core_nodes(self):
             interface=niu.Function(
                 input_names="dwi_file",
                 output_names=self.get_output_fields(),
-                function=utils.get_caps_filenames,
+                function=get_caps_filenames,
             ),
         )
         self.connect(

clinica/pipelines/dwi_dti/__init__.py

@@ -1 +1 @@
-from . import dwi_dti_cli
+from . import cli

clinica/pipelines/dwi_dti/dwi_dti_cli.py → clinica/pipelines/dwi_dti/cli.py

@@ -33,7 +33,7 @@ def cli(
 
     from clinica.utils.ux import print_end_pipeline
 
-    from .dwi_dti_pipeline import DwiDti
+    from .pipeline import DwiDti
 
     pipeline = DwiDti(
         caps_directory=caps_directory,

clinica/pipelines/dwi_dti/dwi_dti_pipeline.py → clinica/pipelines/dwi_dti/pipeline.py

@@ -129,7 +129,7 @@ def _build_output_node(self):
 
         from clinica.utils.nipype import container_from_filename, fix_join
 
-        from .dwi_dti_utils import rename_into_caps
+        from .utils import rename_into_caps
 
         # Find container path from filename
         container_path = npe.Node(
@@ -241,7 +241,6 @@ def _build_output_node(self):
 
     def _build_core_nodes(self):
         """Build and connect the core nodes of the pipeline."""
-        import os
         from pathlib import Path
 
         import nipype.interfaces.fsl as fsl
@@ -255,7 +254,7 @@ def _build_core_nodes(self):
         from clinica.utils.check_dependency import check_environment_variable
         from clinica.utils.dwi import extract_bids_identifier_from_filename
 
-        from .dwi_dti_utils import (
+        from .utils import (
             get_ants_transforms,
             get_caps_filenames,
             print_begin_pipeline,

clinica/pipelines/dwi_dti/dwi_dti_utils.py → clinica/pipelines/dwi_dti/utils.py

@@ -10,7 +10,7 @@ def statistics_on_atlases(in_registered_map, name_map, prefix_file=None):
     Returns:
         List of paths leading to the statistics TSV files.
     """
-    import os
+    from pathlib import Path
 
     from nipype.utils.filemanip import split_filename
 
@@ -41,8 +41,7 @@ def statistics_on_atlases(in_registered_map, name_map, prefix_file=None):
                 f"_res-{atlas.get_spatial_resolution()}_map-{name_map}_statistics.tsv"
             )
 
-        out_atlas_statistics = os.path.abspath(os.path.join(os.getcwd(), filename))
-
+        out_atlas_statistics = str((Path.cwd() / filename).resolve())
         statistics_on_atlas(in_registered_map, atlas, out_atlas_statistics)
         atlas_statistics_list.append(out_atlas_statistics)
 

clinica/pipelines/dwi_preprocessing_using_fmap/__init__.py

@@ -1 +1 @@
-from . import dwi_preprocessing_using_phasediff_fmap_cli
+from . import cli

clinica/pipelines/dwi_preprocessing_using_fmap/dwi_preprocessing_using_phasediff_fmap_cli.py → clinica/pipelines/dwi_preprocessing_using_fmap/cli.py

@@ -41,9 +41,7 @@ def cli(
 
     from clinica.utils.ux import print_end_pipeline
 
-    from .dwi_preprocessing_using_phasediff_fmap_pipeline import (
-        DwiPreprocessingUsingPhaseDiffFMap,
-    )
+    from .pipeline import DwiPreprocessingUsingPhaseDiffFMap
 
     parameters = {
         "low_bval": low_bval,

clinica/pipelines/dwi_preprocessing_using_fmap/dwi_preprocessing_using_phasediff_fmap_pipeline.py → clinica/pipelines/dwi_preprocessing_using_fmap/pipeline.py

@@ -175,7 +175,7 @@ def _build_output_node(self):
 
         from clinica.utils.nipype import container_from_filename, fix_join
 
-        from .dwi_preprocessing_using_phasediff_fmap_utils import rename_into_caps
+        from .utils import rename_into_caps
 
         container_path = npe.Node(
             nutil.Function(
@@ -261,19 +261,13 @@ def _build_core_nodes(self):
         import nipype.interfaces.utility as nutil
         import nipype.pipeline.engine as npe
 
-        from clinica.pipelines.dwi_preprocessing_using_t1.dwi_preprocessing_using_t1_workflows import (
+        from clinica.pipelines.dwi_preprocessing_using_t1.workflows import (
             eddy_fsl_pipeline,
         )
         from clinica.utils.dwi import compute_average_b0
 
-        from .dwi_preprocessing_using_phasediff_fmap_utils import (
-            init_input_node,
-            print_end_pipeline,
-        )
-        from .dwi_preprocessing_using_phasediff_fmap_workflows import (
-            calibrate_and_register_fmap,
-            compute_reference_b0,
-        )
+        from .utils import init_input_node, print_end_pipeline
+        from .workflows import calibrate_and_register_fmap, compute_reference_b0
 
         init_node = npe.Node(
             interface=nutil.Function(

clinica/pipelines/dwi_preprocessing_using_fmap/dwi_preprocessing_using_phasediff_fmap_utils.py → clinica/pipelines/dwi_preprocessing_using_fmap/utils.py

@@ -170,41 +170,39 @@ def rads2hz(in_file: str, delta_te: float, out_file: str = None) -> str:
         Path to output file.
     """
     import math
-    import os
 
     import nibabel as nb
     import numpy as np
 
-    if out_file is None:
-        fname, fext = os.path.splitext(os.path.basename(in_file))
-        if fext == ".gz":
-            fname, _ = os.path.splitext(fname)
-        out_file = os.path.abspath(f"./{fname}_radsec.nii.gz")
-
     im = nb.load(in_file)
+    out_file = out_file or _get_output_file(in_file, "radsec")
     data = im.get_fdata().astype(np.float32) * (1.0 / (float(delta_te) * 2 * math.pi))
     nb.Nifti1Image(data, im.affine, im.header).to_filename(out_file)
 
     return out_file
 
 
+def _get_output_file(input_file: str, suffix: str) -> str:
+    from pathlib import Path
+
+    input_file = Path(input_file)
+    filename = input_file.name
+    if input_file.suffix == ".gz":
+        filename = Path(filename).name
+
+    return str(Path(f"./{filename}_{suffix}.nii.gz").resolve())
+
+
 def demean_image(in_file: str, in_mask: str = None, out_file: str = None) -> str:
     """Demean image data inside mask.
 
     This function was taken from: https://github.com/niflows/nipype1-workflows/
     """
-    import os.path as op
-
     import nibabel as nb
     import numpy as np
 
-    if out_file is None:
-        fname, fext = op.splitext(op.basename(in_file))
-        if fext == ".gz":
-            fname, _ = op.splitext(fname)
-        out_file = op.abspath("./%s_demean.nii.gz" % fname)
-
     im = nb.load(in_file)
+    out_file = out_file or _get_output_file(in_file, "demean")
     data = im.get_fdata().astype(np.float32)
     mask = np.ones_like(data)
 
@@ -216,6 +214,7 @@ def demean_image(in_file: str, in_mask: str = None, out_file: str = None) -> str
     mean = np.median(data[mask == 1].reshape(-1))
     data[mask == 1] = data[mask == 1] - mean
     nb.Nifti1Image(data, im.affine, im.header).to_filename(out_file)
+
     return out_file
 
 
@@ -225,17 +224,11 @@ def siemens2rads(in_file: str, out_file: str = None):
     This function was taken from: https://github.com/niflows/nipype1-workflows/
     """
     import math
-    import os.path as op
 
     import nibabel as nb
     import numpy as np
 
-    if out_file is None:
-        fname, fext = op.splitext(op.basename(in_file))
-        if fext == ".gz":
-            fname, _ = op.splitext(fname)
-        out_file = op.abspath("./%s_rads.nii.gz" % fname)
-
+    out_file = out_file or _get_output_file(in_file, "rads")
     in_file = np.atleast_1d(in_file).tolist()
     im = nb.load(in_file[0])
     data = im.get_fdata().astype(np.float32)

clinica/pipelines/dwi_preprocessing_using_fmap/dwi_preprocessing_using_phasediff_fmap_workflows.py → clinica/pipelines/dwi_preprocessing_using_fmap/workflows.py

@@ -110,15 +110,11 @@ def prepare_phasediff_fmap(
     import nipype.interfaces.utility as nutil
     import nipype.pipeline.engine as npe
 
-    from clinica.pipelines.dwi_preprocessing_using_fmap.dwi_preprocessing_using_phasediff_fmap_workflows import (
-        cleanup_edge_pipeline,
+    from clinica.pipelines.dwi_preprocessing_using_fmap.workflows import (
+        cleanup_edge_pipeline,  # noqa
     )
 
-    from .dwi_preprocessing_using_phasediff_fmap_utils import (
-        demean_image,
-        rads2hz,
-        siemens2rads,
-    )
+    from .utils import demean_image, rads2hz, siemens2rads
 
     input_node = npe.Node(
         nutil.IdentityInterface(
@@ -271,12 +267,10 @@ def compute_reference_b0(
     import nipype.interfaces.utility as niu
     import nipype.pipeline.engine as npe
 
-    from clinica.pipelines.dwi_preprocessing_using_t1.dwi_preprocessing_using_t1_workflows import (
-        eddy_fsl_pipeline,
-    )
+    from clinica.pipelines.dwi_preprocessing_using_t1.workflows import eddy_fsl_pipeline
     from clinica.utils.dwi import compute_average_b0
 
-    from .dwi_preprocessing_using_phasediff_fmap_utils import get_grad_fsl
+    from .utils import get_grad_fsl
 
     inputnode = npe.Node(
         niu.IdentityInterface(

clinica/pipelines/dwi_preprocessing_using_t1/__init__.py

@@ -1 +1 @@
-from . import dwi_preprocessing_using_t1_cli
+from . import cli

clinica/pipelines/dwi_preprocessing_using_t1/dwi_preprocessing_using_t1_cli.py → clinica/pipelines/dwi_preprocessing_using_t1/cli.py

@@ -45,7 +45,7 @@ def cli(
 
     from clinica.utils.ux import print_end_pipeline
 
-    from .dwi_preprocessing_using_t1_pipeline import DwiPreprocessingUsingT1
+    from .pipeline import DwiPreprocessingUsingT1
 
     parameters = {
         "low_bval": low_bval,

clinica/pipelines/dwi_preprocessing_using_t1/dwi_preprocessing_using_t1_pipeline.py → clinica/pipelines/dwi_preprocessing_using_t1/pipeline.py

@@ -148,7 +148,7 @@ def _build_output_node(self):
 
         from clinica.utils.nipype import container_from_filename, fix_join
 
-        from .dwi_preprocessing_using_t1_utils import rename_into_caps
+        from .utils import rename_into_caps
 
         container_path = npe.Node(
             nutil.Function(
@@ -210,15 +210,12 @@ def _build_core_nodes(self):
 
         from clinica.utils.dwi import compute_average_b0_task
 
-        from .dwi_preprocessing_using_t1_utils import (
+        from .utils import (
             init_input_node,
             prepare_reference_b0_task,
             print_end_pipeline,
         )
-        from .dwi_preprocessing_using_t1_workflows import (
-            eddy_fsl_pipeline,
-            epi_pipeline,
-        )
+        from .workflows import eddy_fsl_pipeline, epi_pipeline
 
         # Nodes creation
         # ==============