Update base.py

src/fmripost_aroma/workflows/base.py

@@ -349,11 +349,13 @@ def init_single_subject_wf(subject_id: str):
             ica_aroma_wf.inputs.inputnode.bold_mask_std = functional_cache['bold_mask_std']
             workflow.add_nodes([ica_aroma_wf])
 
-        functional_cache['skip_vols'] = (
-            config.workflow.dummy_scans or functional_cache['skip_vols']
-        )
+        if config.workflow.dummy_scans is not None:
+            skip_vols = config.workflow.dummy_scans
+        else:
+            skip_vols = get_nss(functional_cache['confounds'])
+
         ica_aroma_wf.inputs.inputnode.confounds = functional_cache['confounds']
-        ica_aroma_wf.inputs.inputnode.skip_vols = functional_cache['skip_vols']
+        ica_aroma_wf.inputs.inputnode.skip_vols = skip_vols
 
         if config.workflow.denoise_method:
             for space in spaces:
@@ -393,3 +395,24 @@ def clean_datasinks(workflow: pe.Workflow) -> pe.Workflow:
         if node.split('.')[-1].startswith('ds_'):
             workflow.get_node(node).interface.out_path_base = ''
     return workflow
+
+
+def get_nss(confounds_file):
+    """Get number of non-steady state volumes."""
+    import numpy as np
+    import pandas as pd
+
+    df = pd.read_table(confounds_file)
+
+    nss_cols = [c for c in df.columns if c.startswith("non_steady_state_outlier")]
+
+    dummy_scans = 0
+    if nss_cols:
+        initial_volumes_df = df[nss_cols]
+        dummy_scans = np.any(initial_volumes_df.to_numpy(), axis=1)
+        dummy_scans = np.where(dummy_scans)[0]
+
+        # reasonably assumes all NSS volumes are contiguous
+        dummy_scans = int(dummy_scans[-1] + 1)
+
+    return dummy_scans