cleaned up inline python tasks

tclose · tclose · commit bea2b7372a3c · 2025-06-27T13:15:03.000+10:00
diff --git a/pydra/tasks/mriqc/interfaces/bids/iqm_file_sink.py b/pydra/tasks/mriqc/interfaces/bids/iqm_file_sink.py
@@ -82,7 +82,7 @@ def function(
             self_dict["_always_run"] = True
         self_dict = {}
         out_file = _gen_outfile(
-            dismiss_entities=dismiss_entities, out_dir=out_dir, in_file=in_file
+            in_file=in_file, out_dir=out_dir, dismiss_entities=dismiss_entities
         )
 
         if root is not attrs.NOTHING:
@@ -158,7 +158,7 @@ def _add_field(name, value=attrs.NOTHING, _outputs=None, add_trait=None):
     return value
 
 
-def _gen_outfile(dismiss_entities=None, out_dir=None, in_file=None):
+def _gen_outfile(in_file=None, out_dir=None, dismiss_entities=None):
     out_dir = Path()
     if out_dir is not attrs.NOTHING:
         out_dir = Path(out_dir)
diff --git a/pydra/tasks/mriqc/workflows/anatomical/base.py b/pydra/tasks/mriqc/workflows/anatomical/base.py
@@ -140,11 +140,11 @@ def anat_qc_workflow(
     # 4. Spatial Normalization, using ANTs
     norm = workflow.add(
         spatial_normalization(
-            wf_species=wf_species,
             nipype_omp_nthreads=nipype_omp_nthreads,
             wf_template_id=wf_template_id,
             exec_ants_float=exec_ants_float,
             exec_debug=exec_debug,
+            wf_species=wf_species,
             modality=modality,
             name="norm",
         )
@@ -186,9 +186,9 @@ def anat_qc_workflow(
     # Reports
     anat_report_wf = workflow.add(
         init_anat_report_wf(
+            wf_species=wf_species,
             exec_verbose_reports=exec_verbose_reports,
             exec_work_dir=exec_work_dir,
-            wf_species=wf_species,
             in_ras=to_ras.out_file,
             headmask=hmsk.out_file,
             airmask=amw.air_mask,
@@ -225,13 +225,13 @@ def anat_qc_workflow(
         # fmt: on
     outputs_["norm_report"] = norm.report
     outputs_["iqmswf_noise_report"] = iqmswf.noise_report
-    outputs_["anat_report_wf_airmask_report"] = anat_report_wf.airmask_report
-    outputs_["anat_report_wf_bg_report"] = anat_report_wf.bg_report
+    outputs_["anat_report_wf_segm_report"] = anat_report_wf.segm_report
     outputs_["anat_report_wf_bmask_report"] = anat_report_wf.bmask_report
     outputs_["anat_report_wf_artmask_report"] = anat_report_wf.artmask_report
-    outputs_["anat_report_wf_zoom_report"] = anat_report_wf.zoom_report
+    outputs_["anat_report_wf_airmask_report"] = anat_report_wf.airmask_report
+    outputs_["anat_report_wf_bg_report"] = anat_report_wf.bg_report
     outputs_["anat_report_wf_headmask_report"] = anat_report_wf.headmask_report
-    outputs_["anat_report_wf_segm_report"] = anat_report_wf.segm_report
+    outputs_["anat_report_wf_zoom_report"] = anat_report_wf.zoom_report
 
     return tuple(outputs_)
 
@@ -327,32 +327,19 @@ def _select_wm(inlist):
         return [f for f in inlist if "WM" in f][0]
 
     enhance = workflow.add(
-        python.define(
-            _enhance,
-            inputs={"in_file": ty.Any, "wm_tpm": ty.Any},
-            outputs={"out_file": ty.Any},
-        )(in_file=in_file, wm_tpm=in_tpms),
+        python.define(_enhance, outputs=["out_file"])(in_file=in_file, wm_tpm=in_tpms),
         name="enhance",
     )
     gradient = workflow.add(
-        python.define(
-            image_gradient,
-            inputs={"in_file": ty.Any, "brainmask": ty.Any, "sigma": ty.Any},
-            outputs={"out_file": ty.Any},
-        )(brainmask=brainmask, in_file=enhance.out_file),
+        python.define(image_gradient, outputs=["out_file"])(
+            brainmask=brainmask, in_file=enhance.out_file
+        ),
         name="gradient",
     )
     thresh = workflow.add(
-        python.define(
-            gradient_threshold,
-            inputs={
-                "in_file": ty.Any,
-                "brainmask": ty.Any,
-                "aniso": ty.Any,
-                "thresh": ty.Any,
-            },
-            outputs={"out_file": ty.Any},
-        )(brainmask=brainmask, in_file=gradient.out_file),
+        python.define(gradient_threshold, outputs=["out_file"])(
+            brainmask=brainmask, in_file=gradient.out_file
+        ),
         name="thresh",
     )
     if wf_species != "human":
@@ -420,11 +407,7 @@ def _format_tpm_names(in_files, fname_string=None):
         return file_format, out_files
 
     format_tpm_names = workflow.add(
-        python.define(
-            _format_tpm_names,
-            inputs={"in_files": ty.Any},
-            outputs={"file_format": ty.Any},
-        )(
+        python.define(_format_tpm_names, outputs=["file_format"])(
             execution={"keep_inputs": True, "remove_unnecessary_outputs": False},
             in_files=std_tpms,
         ),
@@ -582,7 +565,7 @@ def compute_iqms(
     # Add provenance
 
     # AFNI check smoothing
-    fwhm_interface = get_fwhmx()
+    fwhm_task = get_fwhmx()
     fwhm = workflow.add(fwhm_task, name="fwhm")
     # Harmonize
     homog = workflow.add(
@@ -624,7 +607,10 @@ def _getwm(inlist):
     def fwhm_fwhm_to_measures_in_fwhm_callable(in_: ty.Any) -> ty.Any:
         return _tofloat(in_)
 
-    fwhm_fwhm_to_measures_in_fwhm_callable = workflow.add(fwhm_fwhm_to_measures_in_fwhm_callable(in_=fwhm.fwhm), name="fwhm_fwhm_to_measures_in_fwhm_callable")
+    fwhm_fwhm_to_measures_in_fwhm_callable = workflow.add(
+        fwhm_fwhm_to_measures_in_fwhm_callable(in_=fwhm.fwhm),
+        name="fwhm_fwhm_to_measures_in_fwhm_callable"
+    )
 
     measures.inputs.in_fwhm = fwhm_fwhm_to_measures_in_fwhm_callable.out
     outputs_['measures'] = measures.out_qc
diff --git a/pydra/tasks/mriqc/workflows/diffusion/base.py b/pydra/tasks/mriqc/workflows/diffusion/base.py
@@ -200,12 +200,12 @@ def dmri_qc_workflow(
     # EPI to MNI registration
     spatial_norm = workflow.add(
         epi_mni_align(
-            wf_species=wf_species,
-            nipype_omp_nthreads=nipype_omp_nthreads,
             nipype_nprocs=nipype_nprocs,
+            nipype_omp_nthreads=nipype_omp_nthreads,
             wf_template_id=wf_template_id,
             exec_ants_float=exec_ants_float,
             exec_debug=exec_debug,
+            wf_species=wf_species,
             epi_mean=dwi_ref.out_file,
             epi_mask=dmri_bmsk.out_mask,
             name="spatial_norm",
@@ -240,10 +240,10 @@ def dmri_qc_workflow(
     # Generate outputs
     dwi_report_wf = workflow.add(
         init_dwi_report_wf(
+            wf_fd_thres=wf_fd_thres,
             exec_verbose_reports=exec_verbose_reports,
             exec_work_dir=exec_work_dir,
             wf_species=wf_species,
-            wf_fd_thres=wf_fd_thres,
             wf_biggest_file_gb=wf_biggest_file_gb,
             in_bdict=shells.b_dict,
             brain_mask=dmri_bmsk.out_mask,
@@ -304,14 +304,14 @@ def averages_out_file_to_iqms_wf_in_b0_callable(in_: ty.Any) -> ty.Any:
     # fmt: on
     outputs_["iqms_wf_out_file"] = iqms_wf.out_file
     outputs_["iqms_wf_noise_floor"] = iqms_wf.noise_floor
+    outputs_["dwi_report_wf_fa_report"] = dwi_report_wf.fa_report
     outputs_["dwi_report_wf_heatmap_report"] = dwi_report_wf.heatmap_report
     outputs_["dwi_report_wf_spikes_report"] = dwi_report_wf.spikes_report
-    outputs_["dwi_report_wf_fa_report"] = dwi_report_wf.fa_report
+    outputs_["dwi_report_wf_bmask_report"] = dwi_report_wf.bmask_report
     outputs_["dwi_report_wf_carpet_report"] = dwi_report_wf.carpet_report
     outputs_["dwi_report_wf_md_report"] = dwi_report_wf.md_report
     outputs_["dwi_report_wf_noise_report"] = dwi_report_wf.noise_report
     outputs_["dwi_report_wf_snr_report"] = dwi_report_wf.snr_report
-    outputs_["dwi_report_wf_bmask_report"] = dwi_report_wf.bmask_report
 
     return tuple(outputs_)
 
diff --git a/pydra/tasks/mriqc/workflows/functional/base.py b/pydra/tasks/mriqc/workflows/functional/base.py
@@ -231,10 +231,7 @@ def hmc(
     )
     # Apply transforms to other echos
     apply_hmc = workflow.add(
-        python.define(
-            _apply_transforms,
-            inputs={"in_file": ty.Any, "in_xfm": ty.Any, "max_concurrent": ty.Any},
-        )(in_xfm=estimate_hm.oned_matrix_save),
+        python.define(_apply_transforms)(in_xfm=estimate_hm.oned_matrix_save),
         name="apply_hmc",
     )
     apply_hmc.inputs.inputs.max_concurrent = 4
@@ -433,9 +430,7 @@ def fwhm_fwhm_to_measures_in_fwhm_callable(in_: ty.Any) -> ty.Any:
 
         spikes_fft = workflow.add(
             python.define(
-                slice_wise_fft,
-                inputs={"in_file": ty.Any},
-                outputs={"n_spikes": ty.Any, "out_spikes": ty.Any, "out_fft": ty.Any},
+                slice_wise_fft, outputs=["n_spikes", "out_spikes", "out_fft"]
             )(),
             name="spikes_fft",
         )
@@ -605,8 +600,8 @@ def fmri_qc_workflow(
         hmc(
             omp_nthreads=nipype_omp_nthreads,
             wf_deoblique=wf_deoblique,
-            wf_biggest_file_gb=wf_biggest_file_gb,
             wf_despike=wf_despike,
+            wf_biggest_file_gb=wf_biggest_file_gb,
             in_file=sanitize.out_file,
             name="hmcwf",
         )
@@ -623,20 +618,20 @@ def fmri_qc_workflow(
     # EPI to MNI registration
     ema = workflow.add(
         epi_mni_align(
-            wf_species=wf_species,
-            nipype_omp_nthreads=nipype_omp_nthreads,
             nipype_nprocs=nipype_nprocs,
+            nipype_omp_nthreads=nipype_omp_nthreads,
             wf_template_id=wf_template_id,
             exec_ants_float=exec_ants_float,
             exec_debug=exec_debug,
+            wf_species=wf_species,
             name="ema",
         )
     )
     # 7. Compute IQMs
     iqmswf = workflow.add(
         compute_iqms(
-            wf_biggest_file_gb=wf_biggest_file_gb,
             wf_fft_spikes_detector=wf_fft_spikes_detector,
+            wf_biggest_file_gb=wf_biggest_file_gb,
             in_ras=sanitize.out_file,
             epi_mean=mean.out_file,
             hmc_epi=hmcwf.out_file,
@@ -650,9 +645,9 @@ def fmri_qc_workflow(
         init_func_report_wf(
             exec_verbose_reports=exec_verbose_reports,
             exec_work_dir=exec_work_dir,
+            wf_fft_spikes_detector=wf_fft_spikes_detector,
             wf_species=wf_species,
             wf_biggest_file_gb=wf_biggest_file_gb,
-            wf_fft_spikes_detector=wf_fft_spikes_detector,
             meta_sidecar=metadata,
             in_ras=sanitize.out_file,
             epi_mean=mean.out_file,
@@ -705,12 +700,7 @@ def mean_out_file_to_skullstrip_epi_in_files_callable(in_: ty.Any) -> ty.Any:
         from pydra.tasks.mriqc.workflows.anatomical.base import _binarize
 
         binarise_labels = workflow.add(
-            python.define(
-                _binarize,
-                inputs={"in_file": ty.Any, "threshold": ty.Any},
-                outputs={"out_file": ty.Any},
-            )(),
-            name="binarise_labels",
+            python.define(_binarize, outputs=["out_file"])(), name="binarise_labels"
         )
         # fmt: off
         binarise_labels.inputs.in_file = ema.epi_parc
@@ -726,17 +716,17 @@ def mean_out_file_to_skullstrip_epi_in_files_callable(in_: ty.Any) -> ty.Any:
         outputs_['iqmswf_out_file'] = iqmswf.out_file
         # fmt: on
     outputs_["ema_report"] = ema.report
-    outputs_["iqmswf_outliers"] = iqmswf.outliers
-    outputs_["iqmswf_spikes"] = iqmswf.spikes
     outputs_["iqmswf_out_file"] = iqmswf.out_file
-    outputs_["iqmswf_spikes_num"] = iqmswf.spikes_num
-    outputs_["iqmswf_fft"] = iqmswf.fft
     outputs_["iqmswf_dvars"] = iqmswf.dvars
-    outputs_["func_report_wf_carpet_report"] = func_report_wf.carpet_report
+    outputs_["iqmswf_outliers"] = iqmswf.outliers
+    outputs_["iqmswf_fft"] = iqmswf.fft
+    outputs_["iqmswf_spikes_num"] = iqmswf.spikes_num
+    outputs_["iqmswf_spikes"] = iqmswf.spikes
+    outputs_["func_report_wf_zoomed_report"] = func_report_wf.zoomed_report
     outputs_["func_report_wf_background_report"] = func_report_wf.background_report
-    outputs_["func_report_wf_spikes_report"] = func_report_wf.spikes_report
-    outputs_["func_report_wf_mean_report"] = func_report_wf.mean_report
+    outputs_["func_report_wf_carpet_report"] = func_report_wf.carpet_report
     outputs_["func_report_wf_stdev_report"] = func_report_wf.stdev_report
-    outputs_["func_report_wf_zoomed_report"] = func_report_wf.zoomed_report
+    outputs_["func_report_wf_mean_report"] = func_report_wf.mean_report
+    outputs_["func_report_wf_spikes_report"] = func_report_wf.spikes_report
 
     return tuple(outputs_)
diff --git a/pydra/tasks/mriqc/workflows/functional/output.py b/pydra/tasks/mriqc/workflows/functional/output.py
@@ -78,11 +78,7 @@ def init_func_report_wf(
     # Set FD threshold
 
     spmask = workflow.add(
-        python.define(
-            spikes_mask,
-            inputs={"in_file": ty.Any, "in_mask": ty.Any},
-            outputs={"out_file": ty.Any, "out_plot": ty.Any},
-        )(in_file=in_ras),
+        python.define(spikes_mask, outputs=["out_file", "out_plot"])(in_file=in_ras),
         name="spmask",
     )
     spikes_bg = workflow.add(
