diff --git a/examples/ctf/ctf_with_headshape_pos/1_preprocess.py b/examples/ctf/ctf_with_headshape_pos/1_preprocess.py
index 23f6717d..f3db02ef 100644
--- a/examples/ctf/ctf_with_headshape_pos/1_preprocess.py
+++ b/examples/ctf/ctf_with_headshape_pos/1_preprocess.py
@@ -24,13 +24,20 @@
     "data/raw/Nottingham/sub-not002/meg/sub-not002_task-resteyesopen_meg.ds",
 ]
 
+# Subject IDs
+subjects = [
+    "sub-not001_task-resteyesopen",
+    "sub-not002_task-resteyesopen",
+]
+
 # Directory to save output to
-outdir = "data/preproc"
+outdir = "data"
 
 # Do preprocessing
 preprocessing.run_proc_batch(
     config,
     inputs,
+    subjects=subjects,
     outdir=outdir,
     overwrite=True,
 )
diff --git a/examples/ctf/ctf_with_headshape_pos/2_coregister.py b/examples/ctf/ctf_with_headshape_pos/2_coregister.py
index 483502b9..f596255f 100644
--- a/examples/ctf/ctf_with_headshape_pos/2_coregister.py
+++ b/examples/ctf/ctf_with_headshape_pos/2_coregister.py
@@ -9,7 +9,7 @@
 
 from osl import source_recon, utils
 
-def save_polhemus_from_pos(src_dir, subject, preproc_file, smri_file, epoch_file):
+def save_polhemus_from_pos(outdir, subject):
     """Saves fiducials/headshape from a pos file."""
 
     # Get path to pos file
@@ -17,7 +17,7 @@ def save_polhemus_from_pos(src_dir, subject, preproc_file, smri_file, epoch_file
     utils.logger.log_or_print(f"Saving polhemus info from {pos_file}")
 
     # Get coreg filenames
-    filenames = source_recon.rhino.get_coreg_filenames(src_dir, subject)
+    filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
 
     # Load in txt file, these values are in cm in polhemus space:
     num_headshape_pnts = int(pd.read_csv(pos_file, header=None).to_numpy()[0])
@@ -53,11 +53,11 @@ def save_polhemus_from_pos(src_dir, subject, preproc_file, smri_file, epoch_file
     np.savetxt(filenames["polhemus_lpa_file"], polhemus_lpa)
     np.savetxt(filenames["polhemus_headshape_file"], polhemus_headshape)
 
-def fix_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_file):
+def fix_headshape_points(outdir, subject, preproc_file, smri_file, epoch_file):
     """Remove headshape points on the nose and neck."""
 
     # Load saved headshape and nasion files
-    filenames = source_recon.rhino.get_coreg_filenames(src_dir, subject)
+    filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
     hs = np.loadtxt(filenames["polhemus_headshape_file"])
     nas = np.loadtxt(filenames["polhemus_nasion_file"])
     lpa = np.loadtxt(filenames["polhemus_lpa_file"])
@@ -100,27 +100,30 @@ def fix_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_file):
 """
 
 # Subject IDs
-subjects = ["sub-not001", "sub-not002"]
+subjects = [
+    "sub-not001_task-resteyesopen",
+    "sub-not002_task-resteyesopen",
+]
 
 # Fif files containing the sensor-level preprocessed data for each subject
 preproc_files = [
-    "data/preproc/sub-not001_task-resteyesopen_meg/sub-not001_task-resteyesopen_meg_preproc_raw.fif",
-    "data/preproc/sub-not002_task-resteyesopen_meg/sub-not002_task-resteyesopen_meg_preproc_raw.fif",
+    "data/sub-not001_task-resteyesopen/sub-not001_task-resteyesopen_preproc-raw.fif",
+    "data/sub-not002_task-resteyesopen/sub-not002_task-resteyesopen_preproc-raw.fif",
 ]
 
 # The corresponding structurals for each subject
 smri_files = [
-    "data/smri/sub-not001_T1w.nii.gz",
-    "data/smri/sub-not002_T1w.nii.gz",
+    "smri/sub-not001_T1w.nii.gz",
+    "smri/sub-not002_T1w.nii.gz",
 ]
 
 # Directory to save output to
-coreg_dir = "data/coreg"
+outdir = "data"
 
 # Source reconstruction
 source_recon.run_src_batch(
     config,
-    src_dir=coreg_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
     smri_files=smri_files,
diff --git a/examples/ctf/ctf_with_headshape_pos/3_source_reconstruct.py b/examples/ctf/ctf_with_headshape_pos/3_source_reconstruct.py
index 7b984cda..b2b70ca7 100644
--- a/examples/ctf/ctf_with_headshape_pos/3_source_reconstruct.py
+++ b/examples/ctf/ctf_with_headshape_pos/3_source_reconstruct.py
@@ -4,22 +4,8 @@
 
 # Authors: Chetan Gohil <chetan.gohil@psych.ox.ac.uk>
 
-import os
-
 from osl import source_recon
 
-# Directories
-coreg_dir = "data/coreg"
-src_dir = "data/src"
-
-# First copy the coregistration directory
-if os.path.exists(src_dir):
-    print(f"Please first delete: {src_dir}")
-    exit()
-cmd = f"cp -r {coreg_dir} {src_dir}"
-print(cmd)
-os.system(cmd)
-
 # Settings
 config = """
     source_recon:
@@ -33,18 +19,24 @@
 """
 
 # Subject IDs
-subjects = ["sub-not001", "sub-not002"]
+subjects = [
+    "sub-not001_task-resteyesopen",
+    "sub-not002_task-resteyesopen",
+]
 
 # Fif files containing the sensor-level preprocessed data for each subject
 preproc_files = [
-    "data/preproc/sub-not001_task-resteyesopen_meg/sub-not001_task-resteyesopen_meg_preproc_raw.fif",
-    "data/preproc/sub-not002_task-resteyesopen_meg/sub-not002_task-resteyesopen_meg_preproc_raw.fif",
+    "data/sub-not001_task-resteyesopen/sub-not001_task-resteyesopen_preproc-raw.fif",
+    "data/sub-not002_task-resteyesopen/sub-not002_task-resteyesopen_preproc-raw.fif",
 ]
 
+# Directory to save output to
+outdir = "data"
+
 # Source reconstruction
 source_recon.run_src_batch(
     config,
-    src_dir=src_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
 )
diff --git a/examples/ctf/ctf_with_headshape_pos/4_sign_flip.py b/examples/ctf/ctf_with_headshape_pos/4_sign_flip.py
index b85a5394..0c9d82a0 100644
--- a/examples/ctf/ctf_with_headshape_pos/4_sign_flip.py
+++ b/examples/ctf/ctf_with_headshape_pos/4_sign_flip.py
@@ -13,12 +13,15 @@
 from osl import source_recon
 
 # Source directory and subjects to sign flip
-src_dir = "data/src"
-subjects = ["sub-not001", "sub-not002"]
+outdir = "data"
+subjects = [
+    "sub-not001_task-resteyesopen",
+    "sub-not002_task-resteyesopen",
+]
 
 # Find a good template subject to align other subjects to
 template = source_recon.find_template_subject(
-    src_dir, subjects, n_embeddings=15, standardize=True
+    outdir, subjects, n_embeddings=15, standardize=True
 )
 
 # Settings
@@ -34,4 +37,4 @@
 """
 
 # Do the sign flipping
-source_recon.run_src_batch(config, src_dir, subjects)
+source_recon.run_src_batch(config, outdir, subjects)
diff --git a/examples/ctf/ctf_with_headshape_pos/5_save_npy.py b/examples/ctf/ctf_with_headshape_pos/5_save_npy.py
index 62030a88..ae7f1760 100644
--- a/examples/ctf/ctf_with_headshape_pos/5_save_npy.py
+++ b/examples/ctf/ctf_with_headshape_pos/5_save_npy.py
@@ -8,7 +8,7 @@
 
 from osl_dynamics.data import Data
 
-files = sorted(glob("data/src/*/sflip_parc-raw.fif"))
+files = sorted(glob("data/*/*_sflip_parc-raw.fif"))
 data = Data(
     files,
     picks="misc",
diff --git a/examples/ctf/ctf_with_smri_fid/1_preprocess.py b/examples/ctf/ctf_with_smri_fid/1_preprocess.py
index 6d00eb23..f30050a8 100644
--- a/examples/ctf/ctf_with_smri_fid/1_preprocess.py
+++ b/examples/ctf/ctf_with_smri_fid/1_preprocess.py
@@ -17,13 +17,17 @@
 # Create a list of paths to files to preprocess
 inputs = ["data/raw/mg04938_BrainampDBS_20170504_01_raw.fif"]
 
+# Subject IDs
+subjects = ["LN_VTA2"]
+
 # Directory to save output to
-outdir = "data/preproc"
+outdir = "data"
 
 # Do preprocessing
 preprocessing.run_proc_batch(
     config,
     inputs,
+    subjects=subjects,
     outdir=outdir,
     overwrite=True,
 )
diff --git a/examples/ctf/ctf_with_smri_fid/2_coregister.py b/examples/ctf/ctf_with_smri_fid/2_coregister.py
index b0c9ac1f..82adf8ab 100644
--- a/examples/ctf/ctf_with_smri_fid/2_coregister.py
+++ b/examples/ctf/ctf_with_smri_fid/2_coregister.py
@@ -25,18 +25,17 @@
 subjects = ["LN_VTA2"]
 
 # Lists for input files
-preproc_files = ["data/preproc/mg04938_BrainampDBS_20170504_01_preproc_raw.fif"]
-smri_files = ["data/smri/LN_VTA2.nii"]
+preproc_files = ["data/LN_VTA2/mg04938_BrainampDBS_20170504_01_preproc-raw.fif"]
+smri_files = ["smri/LN_VTA2.nii"]
 
 # Output directory
-coreg_dir = "data/coreg"
+outdir = "data"
 
 # Do coregistration
 source_recon.run_src_batch(
     config,
-    src_dir=coreg_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
     smri_files=smri_files,
-    extra_funcs=[save_mni_fids],
 )
diff --git a/examples/ctf/ctf_with_smri_fid/3_source_reconstruct.py b/examples/ctf/ctf_with_smri_fid/3_source_reconstruct.py
index 20ccf110..79ee9011 100644
--- a/examples/ctf/ctf_with_smri_fid/3_source_reconstruct.py
+++ b/examples/ctf/ctf_with_smri_fid/3_source_reconstruct.py
@@ -4,22 +4,8 @@
 
 # Authors: Chetan Gohil <chetan.gohil@psych.ox.ac.uk>
 
-import os
-
 from osl import source_recon
 
-# Directories
-coreg_dir = "data/coreg"
-src_dir = "data/src"
-
-# First copy the coregistration directory
-if os.path.exists(src_dir):
-    print(f"Please first delete: {src_dir}")
-    exit()
-cmd = f"cp -r {coreg_dir} {src_dir}"
-print(cmd)
-os.system(cmd)
-
 # Settings
 config = """
     source_recon:
@@ -38,12 +24,15 @@
 subjects = ["LN_VTA2"]
 
 # Fif files containing the sensor-level preprocessed data for each subject
-preproc_files = ["data/preproc/mg04938_BrainampDBS_20170504_01_preproc_raw.fif"]
+preproc_files = ["data/LN_VTA2/mg04938_BrainampDBS_20170504_01_preproc-raw.fif"]
+
+# Directories
+outdir = "data"
 
 # Source reconstruction
 source_recon.run_src_batch(
     config,
-    src_dir=src_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
 )
diff --git a/examples/ctf/ctf_with_smri_fid/4_sign_flip.py b/examples/ctf/ctf_with_smri_fid/4_sign_flip.py
index 371d1a3e..491a1631 100644
--- a/examples/ctf/ctf_with_smri_fid/4_sign_flip.py
+++ b/examples/ctf/ctf_with_smri_fid/4_sign_flip.py
@@ -26,7 +26,7 @@ def load(filename):
 
 
 # Files to sign flip
-files = sorted(glob("data/src/*/parc/parc-raw.fif"))
+files = sorted(glob("data/*/parc/parc-raw.fif"))
 
 # Get covariance matrices
 covs = load_covariances(
diff --git a/examples/elekta/1_maxfilter.py b/examples/elekta/1_maxfilter.py
index 78f4ab92..58787530 100644
--- a/examples/elekta/1_maxfilter.py
+++ b/examples/elekta/1_maxfilter.py
@@ -9,12 +9,12 @@
 
 # Setup paths to raw (pre-maxfiltered) fif files
 input_files = [
-    "data/raw/file1.fif",
-    "data/raw/file2.fif",
+    "raw/file1.fif",
+    "raw/file2.fif",
 ]
 
 # Directory to save the maxfiltered data to
-output_directory = "data/maxfilter"
+output_directory = "maxfilter"
 
 # Run MaxFiltering
 #
diff --git a/examples/elekta/2_preprocess.py b/examples/elekta/2_preprocess.py
index 1f77f339..dea8cdfb 100644
--- a/examples/elekta/2_preprocess.py
+++ b/examples/elekta/2_preprocess.py
@@ -10,8 +10,8 @@
 from osl import preprocessing, utils
 
 # Files and directories
-raw_file = "data/maxfilter/{subject}_tsss.fif"  # {subject} will be replace by the name for the subject
-preproc_dir = "data/preproc"  # output directory containing the preprocess files
+raw_file = "maxfilter/{subject}_tsss.fif"  # {subject} will be replace by the name for the subject
+outdir = "data"
 
 subjects = ["sub-001", "sub-002"]
 
@@ -50,7 +50,8 @@
     preprocessing.run_proc_batch(
         config,
         inputs,
-        outdir=preproc_dir,
+        subjects=subjects,
+        outdir=outdir,
         overwrite=True,
         dask_client=True,
     )
diff --git a/examples/elekta/3_coregister.py b/examples/elekta/3_coregister.py
index 10ffba20..1d60f3aa 100644
--- a/examples/elekta/3_coregister.py
+++ b/examples/elekta/3_coregister.py
@@ -17,13 +17,12 @@
 from osl import source_recon, utils
 
 # Directories
-preproc_dir = "data/preproc"
-anat_dir = "data/smri"
-coreg_dir = "data/coreg"
+outdir = "data"
+anatdir = "smri"
 
 # Files ({subject} will be replaced by the name for the subject)
-preproc_file = preproc_dir + "/{subject}_tsss_preproc_raw.fif"
-smri_file = anat_dir + "/{subject}/anat/{subject}_T1w.nii"
+preproc_file = outdir + "{subject}/{subject}_tsss_preproc-raw.fif"
+smri_file = anatdir + "/{subject}/anat/{subject}_T1w.nii"
 
 # Subjects to coregister
 subjects = ["sub-001", "sub-002"]
@@ -60,7 +59,7 @@
     # Run coregistration
     source_recon.run_src_batch(
         config,
-        src_dir=coreg_dir,
+        outdir=outdir,
         subjects=subjects,
         preproc_files=preproc_files,
         smri_files=smri_files,
diff --git a/examples/elekta/4_source_reconstruct.py b/examples/elekta/4_source_reconstruct.py
index e79450ad..1064db95 100644
--- a/examples/elekta/4_source_reconstruct.py
+++ b/examples/elekta/4_source_reconstruct.py
@@ -13,12 +13,10 @@
 from osl import source_recon, utils
 
 # Directories
-preproc_dir = "data/preproc"
-coreg_dir = "data/coreg"
-src_dir = "data/src"
+outdir = "data"
 
 # Files
-preproc_file = preproc_dir + "/{subject}_tsss_preproc_raw.fif"  # {subject} will be replaced by the subject name
+preproc_file = outdir + "/{subject}_tsss_preproc-raw.fif"  # {subject} will be replaced by the subject name
 
 # Subjects to do
 subjects = ["sub-001", "sub-002"]
@@ -40,12 +38,6 @@
 if __name__ == "__main__":
     utils.logger.set_up(level="INFO")
 
-    # Copy directory containing the coregistration
-    if not os.path.exists(src_dir):
-        cmd = f"cp -r {coreg_dir} {src_dir}"
-        print(cmd)
-        os.system(cmd)
-
     # Get paths to files
     preproc_files = []
     for subject in subjects:
@@ -60,7 +52,7 @@
     # Source reconstruction
     source_recon.run_src_batch(
         config,
-        src_dir=src_dir,
+        outdir=outdir,
         subjects=subjects,
         preproc_files=preproc_files,
         dask_client=True,
diff --git a/examples/elekta/5_sign_flip.py b/examples/elekta/5_sign_flip.py
index 870e4af6..8b6a2bf8 100644
--- a/examples/elekta/5_sign_flip.py
+++ b/examples/elekta/5_sign_flip.py
@@ -11,7 +11,7 @@
 from osl.source_recon import find_template_subject, run_src_batch
 
 # Directories
-src_dir = "data/src"
+outdir = "data"
 
 if __name__ == "__main__":
     utils.logger.set_up(level="INFO")
@@ -19,7 +19,7 @@
     # Subjects to sign flip
     # We create a list by looking for subjects that have a parc/parc-raw.fif file
     subjects = []
-    for path in sorted(glob(src_dir + "/*/parc/parc-raw.fif")):
+    for path in sorted(glob(f"{outdir}/*/parc/parc-raw.fif")):
         subject = path.split("/")[-3]
         subjects.append(subject)
 
@@ -49,7 +49,7 @@
     # Do the sign flipping
     run_src_batch(
         config,
-        src_dir=src_dir,
+        outdir=outdir,
         subjects=subjects,
         dask_client=True,
     )
diff --git a/examples/opm/1_preprocess.py b/examples/opm/1_preprocess.py
index 23da9bf5..6f4f05d1 100644
--- a/examples/opm/1_preprocess.py
+++ b/examples/opm/1_preprocess.py
@@ -16,15 +16,19 @@
 """
 
 # List of fif files to preprocess
-inputs = ["data/raw/13703-braille_test-meg.fif"]
+inputs = ["raw/13703-braille_test-meg.fif"]
+
+# Subject IDs
+subjects = ["13703"]
 
 # Directory to save output to
-outdir = "data/preproc"
+outdir = "data"
 
 # Do preprocessing
 dataset = preprocessing.run_proc_batch(
     config,
     inputs,
+    subjects=subjects,
     outdir=outdir,
     overwrite=True,
 )
diff --git a/examples/opm/2_coregister.py b/examples/opm/2_coregister.py
index 76864080..1fd4bb7f 100644
--- a/examples/opm/2_coregister.py
+++ b/examples/opm/2_coregister.py
@@ -8,13 +8,13 @@
 
 from osl import source_recon, utils
 
-def coregister(src_dir, subject, preproc_file, smri_file, epoch_file):
+def coregister(outdir, subject, preproc_file):
     """Coregister OPM data."""
 
     # Create dummy coregistration files
     source_recon.rhino.coreg(
         fif_file=preproc_file,
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         use_headshape=False,
         use_nose=False,
@@ -22,7 +22,7 @@ def coregister(src_dir, subject, preproc_file, smri_file, epoch_file):
     )
 
     # Copy head to MRI transformation (needed for the forward model)
-    filenames = source_recon.rhino.get_coreg_filenames(src_dir, subject)
+    filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
     in_file = f"data/raw/{subject}-head_scaledmri-trans.fif"    
     out_file = filenames["head_scaledmri_t_file"]
     cmd = f"cp {in_file} {out_file}"
@@ -44,19 +44,19 @@ def coregister(src_dir, subject, preproc_file, smri_file, epoch_file):
 
 # Fif files containing the sensor-level preprocessed data for each subject
 preproc_files = [
-    "data/preproc/13703-braille_test-meg/13703-braille_test-meg_preproc_raw.fif",
+    "data/13703/13703-braille_test-meg_preproc-raw.fif",
 ]
 
 # The corresponding structurals for each subject
-smri_files = ["data/raw/13703.nii"]
+smri_files = ["raw/13703.nii"]
 
 # Directory to save output to
-outdir = "data/coreg"
+outdir = "data"
 
 # Perform coregistration
 source_recon.run_src_batch(
     config,
-    src_dir=outdir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
     smri_files=smri_files,
diff --git a/examples/opm/3_source_reconstruct.py b/examples/opm/3_source_reconstruct.py
index b944b57e..6cb3d35e 100644
--- a/examples/opm/3_source_reconstruct.py
+++ b/examples/opm/3_source_reconstruct.py
@@ -9,16 +9,7 @@
 from osl import source_recon
 
 # Directories
-coreg_dir = "data/coreg"
-src_dir = "data/src"
-
-# First copy the coregistration directory
-if os.path.exists(src_dir):
-    print(f"Please first delete: {src_dir}")
-    exit()
-cmd = f"cp -r {coreg_dir} {src_dir}"
-print(cmd)
-os.system(cmd)
+outdir = "data"
 
 # Settings
 config = """
@@ -38,13 +29,13 @@
 
 # Fif files containing the sensor-level preprocessed data for each subject
 preproc_files = [
-    "data/preproc/13703-braille_test-meg/13703-braille_test-meg_preproc_raw.fif",
+    "data/13703/13703-braille_test-meg_preproc-raw.fif",
 ]
 
 # Do source reconstruction
 source_recon.run_src_batch(
     config,
-    src_dir=src_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
 )
diff --git a/examples/opm/4_sign_flip.py b/examples/opm/4_sign_flip.py
index feaed527..9b37943e 100644
--- a/examples/opm/4_sign_flip.py
+++ b/examples/opm/4_sign_flip.py
@@ -13,12 +13,12 @@
 from osl import source_recon
 
 # Source directory and subjects to sign flip
-src_dir = "data/src"
+outdir = "data"
 subjects = ["13703"]
 
 # Find a good template subject to align other subjects to
 template = source_recon.find_template_subject(
-    src_dir, subjects, n_embeddings=15, standardize=True
+    outdir, subjects, n_embeddings=15, standardize=True
 )
 
 # Settings
@@ -34,4 +34,4 @@
 """
 
 # Do the sign flipping
-source_recon.run_src_batch(config, src_dir, subjects)
+source_recon.run_src_batch(config, outdir, subjects)
diff --git a/examples/opm/5_save_npy.py b/examples/opm/5_save_npy.py
index 62030a88..ae7f1760 100644
--- a/examples/opm/5_save_npy.py
+++ b/examples/opm/5_save_npy.py
@@ -8,7 +8,7 @@
 
 from osl_dynamics.data import Data
 
-files = sorted(glob("data/src/*/sflip_parc-raw.fif"))
+files = sorted(glob("data/*/*_sflip_parc-raw.fif"))
 data = Data(
     files,
     picks="misc",
diff --git a/examples/parallelisation/parallel_preprocess.py b/examples/parallelisation/parallel_preprocess.py
index 21f4dbd8..de7ada1c 100644
--- a/examples/parallelisation/parallel_preprocess.py
+++ b/examples/parallelisation/parallel_preprocess.py
@@ -14,8 +14,8 @@
 if __name__ == "__main__":
     utils.logger.set_up(level="INFO")
 
-    raw_dir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/meg/pipeline/release005/BIDSsep/rest"
-    preproc_dir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
+    rawdir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/meg/pipeline/release005/BIDSsep/rest"
+    outdir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
 
     config = """
         preproc:
@@ -30,9 +30,9 @@
 
     # Get input files
     inputs = []
-    for subject in glob(raw_dir + "/sub-*"):
+    for subject in sorted(glob(f"{rawdir}/sub-*")):
         subject = pathlib.Path(subject).stem
-        inputs.append(raw_dir + f"/{subject}/ses-rest/meg/{subject}_ses-rest_task-rest_meg.fif")
+        inputs.append(f"{rawdir}/{subject}/ses-rest/meg/{subject}_ses-rest_task-rest_meg.fif")
     inputs = inputs[:2]
 
     # Setup a Dask client for parallel processing
@@ -52,7 +52,7 @@
     preprocessing.run_proc_batch(
         config,
         inputs,
-        outdir=preproc_dir,
+        outdir=outdir,
         overwrite=True,
         dask_client=True,
     )
diff --git a/examples/parallelisation/parallel_source_reconstruct.py b/examples/parallelisation/parallel_source_reconstruct.py
index e6ca9208..6d742452 100644
--- a/examples/parallelisation/parallel_source_reconstruct.py
+++ b/examples/parallelisation/parallel_source_reconstruct.py
@@ -23,13 +23,12 @@
     utils.logger.set_up(level="INFO")
 
     # Directories
-    anat_dir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/mri/pipeline/release004/BIDS_20190411/anat"
-    preproc_dir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
-    src_dir = "/ohba/pi/mwoolrich/cgohil/camcan/src"
+    anatdir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/mri/pipeline/release004/BIDS_20190411/anat"
+    outdir = "/ohba/pi/mwoolrich/cgohil/camcan/src"
 
     # Files
-    SMRI_FILE = anat_dir + "/{0}/anat/{0}_T1w.nii"
-    PREPROC_FILE = preproc_dir + "{0}_ses-rest_task-rest_meg/{0}_ses-rest_task-rest_meg_preproc_raw.fif"
+    smri_file = anatdir + "/{0}/anat/{0}_T1w.nii"
+    preproc_file = outdir + "{0}_ses-rest_task-rest_meg/{0}_ses-rest_task-rest_meg_preproc-raw.fif"
 
     # Settings
     config = """
@@ -52,11 +51,11 @@
             orthogonalisation: symmetric
     """
 
-    def remove_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_file):
+    def remove_headshape_points(outdir, subject):
         """Removes headshape points near the nose."""
 
         # Get coreg filenames
-        filenames = source_recon.rhino.get_coreg_filenames(src_dir, subject)
+        filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
 
         # Load saved headshape and nasion files
         hs = np.loadtxt(filenames["polhemus_headshape_file"])
@@ -104,7 +103,7 @@ def remove_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_fil
     # Beamforming and parcellation
     source_recon.run_src_batch(
         config,
-        src_dir=src_dir,
+        outdir=outdir,
         subjects=subjects,
         preproc_files=preproc_files,
         smri_files=smri_files,
diff --git a/examples/parallelisation/serial_preprocess.py b/examples/parallelisation/serial_preprocess.py
index 89c47525..b4d81553 100644
--- a/examples/parallelisation/serial_preprocess.py
+++ b/examples/parallelisation/serial_preprocess.py
@@ -10,8 +10,8 @@
 
 from osl import preprocessing
 
-raw_dir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/meg/pipeline/release005/BIDSsep/rest"
-preproc_dir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
+rawdir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/meg/pipeline/release005/BIDSsep/rest"
+outdir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
 
 config = """
     preproc:
@@ -26,15 +26,15 @@
 
 # Get input files
 inputs = []
-for subject in glob(raw_dir + "/sub-*"):
+for subject in sorted(glob(f"{rawdir}/sub-*")):
     subject = pathlib.Path(subject).stem
-    inputs.append(raw_dir + f"/{subject}/ses-rest/meg/{subject}_ses-rest_task-rest_meg.fif")
+    inputs.append(f"{rawdir}/{subject}/ses-rest/meg/{subject}_ses-rest_task-rest_meg.fif")
 inputs = inputs[:2]
 
 # Main preprocessing
 preprocessing.run_proc_batch(
     config,
     inputs,
-    outdir=preproc_dir,
+    outdir=outdir,
     overwrite=True,
 )
diff --git a/examples/parallelisation/serial_source_reconstruct.py b/examples/parallelisation/serial_source_reconstruct.py
index 5bffa415..4731cbc2 100644
--- a/examples/parallelisation/serial_source_reconstruct.py
+++ b/examples/parallelisation/serial_source_reconstruct.py
@@ -19,13 +19,12 @@
 logger = logging.getLogger("osl")
 
 # Directories
-anat_dir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/mri/pipeline/release004/BIDS_20190411/anat"
-preproc_dir = "/ohba/pi/mwoolrich/cgohil/camcan/preproc"
-src_dir = "/ohba/pi/mwoolrich/cgohil/camcan/src"
+anatdir = "/ohba/pi/mwoolrich/datasets/CamCan_2021/cc700/mri/pipeline/release004/BIDS_20190411/anat"
+outdir = "/ohba/pi/mwoolrich/cgohil/camcan/src"
 
 # Files
-smri_file = anat_dir + "/{0}/anat/{0}_T1w.nii"
-preproc_file = preproc_dir + "{0}_ses-rest_task-rest_meg/{0}_ses-rest_task-rest_meg_preproc_raw.fif"
+smri_file = anatdir + "/{0}/anat/{0}_T1w.nii"
+preproc_file = outdir + "{0}_ses-rest_task-rest_meg/{0}_ses-rest_task-rest_meg_preproc-raw.fif"
 
 # Settings
 config = """
@@ -48,11 +47,11 @@
         orthogonalisation: symmetric
 """
 
-def remove_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_file):
+def remove_headshape_points(outdir, subject):
     """Removes headshape points near the nose."""
 
     # Get coreg filenames
-    filenames = source_recon.rhino.get_coreg_filenames(src_dir, subject)
+    filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
 
     # Load saved headshape and nasion files
     hs = np.loadtxt(filenames["polhemus_headshape_file"])
@@ -74,7 +73,7 @@ def remove_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_fil
 
 # Get subjects
 subjects = []
-for subject in glob(preproc_dir + "/sub-*"):
+for subject in sorted(glob(f"{outdir}/sub-*")):
     subjects.append(pathlib.Path(subject).stem.split("_")[0])
 
 # Setup files
@@ -87,7 +86,7 @@ def remove_headshape_points(src_dir, subject, preproc_file, smri_file, epoch_fil
 # Beamforming and parcellation
 source_recon.run_src_batch(
     config,
-    src_dir=src_dir,
+    outdir=outdir,
     subjects=subjects,
     preproc_files=preproc_files,
     smri_files=smri_files,
diff --git a/osl/preprocessing/README.md b/osl/preprocessing/README.md
index 2ce82d84..2b005c45 100644
--- a/osl/preprocessing/README.md
+++ b/osl/preprocessing/README.md
@@ -35,7 +35,7 @@ outdir = '/where/do/i/want/my/output_dir'
 # Process a single file
 raw_file = '/path/to/file.fif'
 
-osl.preprocessing.run_proc_chain(config, raw_file, outdir)  # creates /path/to/file_preproc_raw.fif
+osl.preprocessing.run_proc_chain(config, raw_file, outdir)  # creates /path/to/file_preproc-raw.fif
 
 # Process a list of files
 list_of_raw_files = ['/path/to/file1.fif','/path/to/file2.fif','/path/to/file3.fif']
@@ -74,7 +74,7 @@ The following code runs the chain on a file:
 ```
 fname = '/path/to/my/dataset.fif'
 
-osl.preprocessing.run_proc_chain(config, fname)  # creates dataset_preproc_raw.fif and dataset_epo.fif
+osl.preprocessing.run_proc_chain(config, fname)  # creates dataset_preproc-raw.fif and dataset_epo.fif
 
 # Average the epochs object and visualise a response
 epochs = mne.io.read_raw_fif('/path/to/my/dataset_epo.fif')
diff --git a/osl/preprocessing/batch.py b/osl/preprocessing/batch.py
index 2ebeaf7c..18497bc7 100644
--- a/osl/preprocessing/batch.py
+++ b/osl/preprocessing/batch.py
@@ -29,7 +29,7 @@
 import yaml
 
 from . import mne_wrappers, osl_wrappers
-from ..utils import find_run_id, validate_outdir, process_file_inputs, add_subdir
+from ..utils import find_run_id, validate_outdir, process_file_inputs
 from ..utils import logger as osl_logger
 from ..utils.parallel import dask_parallel_bag
 from ..utils.version_utils import check_version
@@ -105,14 +105,17 @@ def import_data(infile, preload=True):
     elif os.path.splitext(infile)[1] == ".fif":
         logger.info("Detected fif file format, using: mne.io.read_raw_fif")
         raw = mne.io.read_raw_fif(infile, preload=preload)
+
     # EDF file
     elif os.path.splitext(infile)[1].lower() == ".edf":
         logger.info("Detected edf file format, using: mne.io.read_raw_edf")
         raw = mne.io.read_raw_edf(infile, preload=preload)
+
     # CTF data in ds directory
     elif os.path.splitext(infile)[1] == ".ds":
         logger.info("Detected CTF file format, using: mne.io.read_raw_ctf")
         raw = mne.io.read_raw_ctf(infile, preload=preload)
+
     elif os.path.splitext(infile)[1] == ".meg4":
         logger.info("Detected CTF file format, using: mne.io.read_raw_ctf")
         raw = mne.io.read_raw_ctf(os.path.dirname(infile), preload=preload)
@@ -134,6 +137,10 @@ def import_data(infile, preload=True):
     elif os.path.splitext(infile)[1] == ".bdf":
         logger.info("Detected BDF file format, using: mne.io.read_raw_bdf")
         raw = mne.io.read_raw_bdf(infile, preload=preload)
+
+    elif os.path.splitext(infile)[1] == ".mff":
+        logger.info("Detected EGI file format, using mne.io.read_raw_egi")
+        raw = mne.io.read_raw_egi(infile, preload=preload)
         
     # Other formats not accepted
     else:
@@ -289,10 +296,8 @@ def check_config_versions(config):
     ------
     AssertionError
         Raised if package version mismatch found in 'version_assert'
-
-    WARNING
+    Warning
         Raised if package version mismatch found in 'version_warn'
-
     """
     config = load_config(config)
 
@@ -380,7 +385,7 @@ def append_preproc_info(dataset, config, extra_funcs=None):
     return dataset
 
 
-def write_dataset(dataset, outbase, run_id, ftype='preproc_raw', overwrite=False):
+def write_dataset(dataset, outbase, run_id, ftype='preproc-raw', overwrite=False):
     """Write preprocessed data to a file.
 
     Will write all keys in the dataset dict to disk with corresponding extensions.
@@ -394,7 +399,7 @@ def write_dataset(dataset, outbase, run_id, ftype='preproc_raw', overwrite=False
     run_id : str
         ID for the output file.
     ftype: str
-        Extension for the fif file (default ``preproc_raw``)
+        Extension for the fif file (default ``preproc-raw``)
     overwrite : bool
         Should we overwrite if the file already exists?
 
@@ -404,8 +409,8 @@ def write_dataset(dataset, outbase, run_id, ftype='preproc_raw', overwrite=False
         The saved fif file name
     """
 
-    # Strip "_preproc_raw" or "_raw" from the run id
-    for string in ["_preproc_raw", "_raw"]:
+    # Strip "_preproc-raw" or "_raw" from the run id
+    for string in ["_preproc-raw", "_raw"]:
         if string in run_id:
             run_id = run_id.replace(string, "")
 
@@ -450,7 +455,7 @@ def read_dataset(fif, preload=False, ftype=None):
     ftype : str
         Extension for the fif file (will be replaced for e.g. ``'_events.npy'`` or 
         ``'_ica.fif'``). If ``None``, we assume the fif file is preprocessed with 
-        OSL and has the extension ``'_preproc_raw'``. If this fails, we guess 
+        OSL and has the extension ``'_preproc-raw'``. If this fails, we guess 
         the extension as whatever comes after the last ``'_'``.
 
     Returns
@@ -466,9 +471,9 @@ def read_dataset(fif, preload=False, ftype=None):
     # Guess extension
     if ftype is None:
         logger.info("Guessing the preproc extension")
-        if "preproc_raw" in fif:
-            logger.info('Assuming fif file type is "preproc_raw"')
-            ftype = "preproc_raw"
+        if "preproc-raw" in fif:
+            logger.info('Assuming fif file type is "preproc-raw"')
+            ftype = "preproc-raw"
         else:
             if len(fif.split("_"))<2:
                 logger.error("Unable to guess the fif file extension")
@@ -478,7 +483,6 @@ def read_dataset(fif, preload=False, ftype=None):
     
     # add extension to fif file name
     ftype = ftype + ".fif"
-     
     
     events = Path(fif.replace(ftype, "events.npy"))
     if events.exists():
@@ -628,8 +632,8 @@ def plot_preproc_flowchart(
 def run_proc_chain(
     config,
     infile,
-    outname=None,
-    ftype='preproc_raw',
+    subject=None,
+    ftype='preproc-raw',
     outdir=None,
     logsdir=None,
     reportdir=None,
@@ -648,19 +652,12 @@ def run_proc_chain(
         Preprocessing config.
     infile : str
         Path to input file.
-    outname : str
-        Output filename.
+    subject : str
+        Subject ID. This will be the sub-directory in outdir.
     ftype: str
-        Extension for the fif file (default ``preproc_raw``)
+        Extension for the fif file (default ``preproc-raw``)
     outdir : str
-        Output directory. If processing multiple files, they can
-        be put in unique sub directories by including ``{x:0}`` at 
-        the end of the outdir, where ``x`` is the pattern which
-        precedes the unique identifier and ``0`` is the length of 
-        the unique identifier. For example: if the outdir is
-        ``../../{sub-:3}`` and each is like 
-        ``/sub-001_task-rest.fif``, the outdir for the file will be
-        ``../../sub-001/``.
+        Output directory.
     logsdir : str
         Directory to save log files to.
     reportdir : str
@@ -687,11 +684,8 @@ def run_proc_chain(
         An empty dict is returned if preprocessing fails. If ``ret_dataset=False``, we return a flag indicating whether preprocessing was successful.
     """
 
-    # Generate a run ID
-    if outname is None:
-        run_id = find_run_id(infile)
-    else:
-        run_id = os.path.splitext(outname)[0]
+    # Get run (subject) ID
+    run_id = subject or find_run_id(infile)
     name_base = "{run_id}_{ftype}.{fext}"
 
     if not ret_dataset:
@@ -706,10 +700,9 @@ def run_proc_chain(
         gen_report = True if gen_report is None else gen_report
         
         # Create output directories if they don't exist
-        outdir = add_subdir(infile, outdir, run_id)
-        outdir = validate_outdir(outdir)
+        outdir = validate_outdir(f"{outdir}/{run_id}")
         logsdir = validate_outdir(logsdir or outdir / "logs")
-        reportdir = validate_outdir(reportdir or outdir / "report")
+        reportdir = validate_outdir(reportdir or outdir / "preproc_report")
 
     else:
         # We're not saving the output to disk
@@ -719,7 +712,7 @@ def run_proc_chain(
         gen_report = gen_report or reportdir is not None or False
         if gen_report:
             # Make sure we have a directory to write the report to
-            reportdir = validate_outdir(reportdir or os.getcwd() + "/report")
+            reportdir = validate_outdir(reportdir or os.getcwd() + "/preproc_report")
 
         # Allow the user to create a log if they pass logsdir
         if logsdir is not None:
@@ -809,6 +802,7 @@ def run_proc_chain(
                 ica=dataset["ica"],
                 preproc_fif_filename=fif_outname,
                 logsdir=logsdir,
+                run_id=run_id,
             )
             gen_html_page(reportdir)
 
@@ -865,7 +859,7 @@ def run_proc_chain(
 def run_proc_batch(
     config,
     files,
-    outnames=None,
+    subjects=None,
     ftype=None,
     outdir=None,
     logsdir=None,
@@ -890,19 +884,12 @@ def run_proc_batch(
     files : str or list or mne.Raw
         Can be a list of Raw objects or a list of filenames (or ``.ds`` dir names if CTF data)
         or a path to a textfile list of filenames (or ``.ds`` dir names if CTF data).
-    outnames: None or list of str
-        output names of the preprocessed files. If None (default), they will be automatically 
-        determined.
+    subjects : list of str
+        Subject directory names. These are sub-directories in outdir.
     ftype: None or str
-        Extension of the preprocessed fif files. Default option is `_preproc_raw`.
+        Extension of the preprocessed fif files. Default option is `_preproc-raw`.
     outdir : str
-        Output directory. If processing multiple files, they can
-        be put in unique sub directories by including ``{x:0}`` at 
-        the end of the outdir, where ``x`` is the pattern which
-        precedes the unique identifier and ``0`` is the length of 
-        the unique identifier. For example: if the outdir is
-        ``../../{sub-:3}`` and each is like ``/sub-001_task-rest.fif``, 
-        the outdir for the file will be ``../../sub-001/``.
+        Output directory.
     logsdir : str
         Directory to save log files to.
     reportdir : str
@@ -945,7 +932,7 @@ def run_proc_batch(
     # Validate the parent outdir - later do so for each subdirectory
     tmpoutdir = validate_outdir(outdir.split('{')[0])
     logsdir = validate_outdir(logsdir or tmpoutdir / "logs")
-    reportdir = validate_outdir(reportdir or tmpoutdir / "report")
+    reportdir = validate_outdir(reportdir or tmpoutdir / "preproc_report")
 
     # Initialise Loggers
     mne.set_log_level(mneverbose)
@@ -961,14 +948,14 @@ def run_proc_batch(
     infiles, good_files_outnames, good_files = process_file_inputs(files)
 
     # Specify filenames for the output data
-    if outnames is None:
-        outnames = good_files_outnames
+    if subjects is None:
+        subjects = good_files_outnames
     else:
-        if len(outnames) != len(good_files_outnames):
+        if len(subjects) != len(good_files_outnames):
             logger.critical(
-                f"Number of outnames ({len(outnames)}) does not match "
+                f"Number of subjects ({len(subjects)}) does not match "
                 f"number of good files {len(good_files_outnames)}. "
-                "Fix outnames or use outnames=None."
+                "Please fix the subjects list or pass subjects=None."
             )
 
     if strictrun and click.confirm('Is this correct set of inputs?') is False:
@@ -1011,8 +998,8 @@ def run_proc_batch(
 
     # Loop through input files to generate arguments for run_proc_chain
     args = []
-    for infile, outname in zip(infiles, outnames):
-        args.append((config, infile, outname))
+    for infile, subject in zip(infiles, subjects):
+        args.append((config, infile, subject))
 
     # Actually run the processes
     if dask_client:
diff --git a/osl/preprocessing/ica_label.py b/osl/preprocessing/ica_label.py
index d853890b..0faa266c 100644
--- a/osl/preprocessing/ica_label.py
+++ b/osl/preprocessing/ica_label.py
@@ -20,15 +20,15 @@
 from ..utils import logger as osl_logger
 
 
-def ica_label(preproc_dir, ica_dir, reject=None, report_dir=None):
+def ica_label(data_dir, subject, reject=None):
     """Data bookkeeping and wrapping plot_ica.
     
     Parameters
     ----------
-    preproc_dir : str
-        Path to preprocessed (M/EEG) data.
-    ica_dir : str
-        Path to ICA data.
+    data_dir : str
+        Path to processed (M/EEG) data.
+    subject : str
+        Subject/session specific data directory name
     reject : bool or str
         If 'all', reject all components (previously labeled and newly
         labeled). If 'manual', reject only manually labeled components. If 
@@ -37,11 +37,16 @@ def ica_label(preproc_dir, ica_dir, reject=None, report_dir=None):
     """
     # global drive, savedir
     plt.ion()
-
-
+    
+    # define data paths based on OSL data structure
+    preproc_file = os.path.join(data_dir, subject, subject + '_preproc-raw.fif')
+    ica_file = os.path.join(data_dir, subject, subject + '_ica.fif')
+    report_dir_base =  os.path.join(data_dir, 'preproc_report')
+    report_dir = os.path.join(report_dir_base, subject + '_preproc-raw')
+    
     print('LOADING DATA')
-    raw = mne.io.read_raw(preproc_dir, preload=True)
-    ica = mne.preprocessing.read_ica(ica_dir)
+    raw = mne.io.read_raw(preproc_file, preload=True)
+    ica = mne.preprocessing.read_ica(ica_file)
     
     # keep these for later
     if reject=='manual':
@@ -64,25 +69,16 @@ def ica_label(preproc_dir, ica_dir, reject=None, report_dir=None):
             new_ica.apply(raw)
             
         print("SAVING PREPROCESSED DATA")
-        raw.save(preproc_dir, overwrite=True)
+        raw.save(preproc_file, overwrite=True)
     
     print("SAVING ICA DATA")
-    ica.save(ica_dir, overwrite=True)
+    ica.save(ica_file, overwrite=True)
     
     if reject is not None:
         print("ATTEMPTING TO UPDATE REPORT")
-        try:
-            if report_dir is None:
-                report_dir = os.path.join("/".join(preproc_dir.split("/")[:-2]), "report")
-            
-            report_dir_base = deepcopy(report_dir)
-            if os.path.exists(os.path.join(report_dir, preproc_dir.split("/")[-2])):
-                report_dir = os.path.join(report_dir, preproc_dir.split("/")[-2])
-            elif os.path.exists(os.path.join(report_dir, preproc_dir.split("/")[-2]).replace("_raw", "") + "_preproc_raw"):
-                report_dir = os.path.join(report_dir, preproc_dir.split("/")[-2]).replace("_raw", "") + "_preproc_raw"
-            print(report_dir)
-            
+        try:           
             savebase = os.path.join(report_dir, "{0}.png")
+            print(report_dir)
             if os.path.exists(os.path.join(report_dir, "ica.png")) or os.path.exists(os.path.join(report_dir, "data.pkl")):
                 _ = plot_bad_ica(raw, ica, savebase)
 
@@ -106,7 +102,7 @@ def ica_label(preproc_dir, ica_dir, reject=None, report_dir=None):
                 print("REPORT UPDATED")
         except:
             print("FAILED TO UPDATE REPORT")
-    print(f'LABELING DATASET {preproc_dir.split("/")[-1]} COMPLETE')
+    print(f'LABELING DATASET {subject} COMPLETE')
 
 
 def main(argv=None):
@@ -123,7 +119,7 @@ def main(argv=None):
     -------
     From the command line (in the OSL environment), use as follows:
 
-    osl_ica_label reject_argument /path/to/preproc_raw.fif [/path/to/ica.fif] [/path/to/reports_dir]
+    osl_ica_label reject_argument /path/to/processed_data subject_name
 
     The `reject_argument` specifies whether to reject 'all' selected components from the data, only
     the 'manual' rejected, or None (and only save the ICA object, without rejecting components). 
@@ -131,7 +127,7 @@ def main(argv=None):
     the usual OSL structure.
     For example:
     
-    osl_ica_label manual /path/to/sub-001_preproc_raw.fif
+    osl_ica_label manual /path/to/proc_dir sub-001_run01
     
     Then use the GUI to label components (click on the time course to mark, use 
     number keys to label marked components as specific artefacts, and use
@@ -149,21 +145,7 @@ def main(argv=None):
     if reject == 'None':
         reject = None
         
-    preproc_dir = argv[1]
-    if len(argv)>2 or (len(argv)==3 and "report" in argv[2]):
-        ica_dir = argv[2]
-    else:
-        ica_dir = preproc_dir.replace('preproc_raw.fif', 'ica.fif')
-
-    if (len(argv)==3 and "report" in argv[2]):
-        report_dir = argv[2]
-    elif (len(argv)==4 and "report" in argv[3]):
-        report_dir = argv[3]
-    else:
-        # try to find it in the directory structure
-        report_dir = None
-        
-    ica_label(preproc_dir, ica_dir, reject, report_dir)
+    ica_label(data_dir=argv[1], subject=argv[2], reject=argv[0])
 
 
 if __name__ == '__main__':
diff --git a/osl/report/preproc_report.py b/osl/report/preproc_report.py
index 0442e5d3..c82cdf71 100644
--- a/osl/report/preproc_report.py
+++ b/osl/report/preproc_report.py
@@ -47,7 +47,7 @@
 # Report generation
 
 
-def gen_report_from_fif(infiles, outdir, ftype=None, logsdir=None):
+def gen_report_from_fif(infiles, outdir, ftype=None, logsdir=None, run_id=None):
     """Generate web-report for a set of MNE data objects.
 
     Parameters
@@ -57,10 +57,12 @@ def gen_report_from_fif(infiles, outdir, ftype=None, logsdir=None):
     outdir : str
         Directory to save HTML report and figures to.
     ftype : str
-        Type of fif file, e.g., ``'raw'`` or ``'preproc_raw'``.
+        Type of fif file, e.g., ``'raw'`` or ``'preproc-raw'``.
     logsdir : str
         Directory the log files were saved into. If None, log files are assumed
         to be in outdir.replace('report', 'logs')
+    run_id : str
+        Run ID.
     """
 
     # Validate input files and directory to save html file and plots to
@@ -73,7 +75,13 @@ def gen_report_from_fif(infiles, outdir, ftype=None, logsdir=None):
         dataset = read_dataset(infile, ftype=ftype)
         run_id = get_header_id(dataset['raw'])
         htmldatadir = validate_outdir(outdir / run_id)
-        gen_html_data(dataset['raw'], htmldatadir, ica=dataset['ica'], logsdir=logsdir)
+        gen_html_data(
+            dataset['raw'],
+            htmldatadir,
+            ica=dataset['ica'],
+            logsdir=logsdir,
+            run_id=run_id,
+        )
 
     # Create report
     gen_html_page(outdir)
@@ -100,7 +108,9 @@ def get_header_id(raw):
     return raw.filenames[0].split('/')[-1].strip('.fif')
 
 
-def gen_html_data(raw, outdir, ica=None, preproc_fif_filename=None, logsdir=None):
+def gen_html_data(
+    raw, outdir, ica=None, preproc_fif_filename=None, logsdir=None, run_id=None
+):
     """Generate HTML web-report for an MNE data object.
 
     Parameters
@@ -116,12 +126,14 @@ def gen_html_data(raw, outdir, ica=None, preproc_fif_filename=None, logsdir=None
     logsdir : str
         Directory the log files were saved into. If None, log files are assumed
         to be in reportdir.replace('report', 'logs')
+    run_id : str
+        Run ID.
     """
 
     data = {}
     data['filename'] = raw.filenames[0]
     data['preproc_fif_filename'] = preproc_fif_filename
-    data['fif_id'] = get_header_id(raw)
+    data['fif_id'] = run_id or get_header_id(raw)
 
     # Scan info
     data['projname'] = raw.info['proj_name']
@@ -254,7 +266,7 @@ def gen_html_data(raw, outdir, ica=None, preproc_fif_filename=None, logsdir=None
     
     # add log files if possible
     if logsdir is None:
-        logsdir = outdir._str.replace('/report/', '/logs/')
+        logsdir = outdir._str.replace('preproc_report', 'logs')
     elif type(logsdir)==pathlib.PosixPath:
         logsdir = os.path.join(logsdir._str, outdir._str.split('/')[-1])
         
@@ -383,7 +395,7 @@ def gen_html_summary(reportdir, logsdir=None):
     
     # log files
     if logsdir is None:
-        logsdir = reportdir._str.replace('report', 'logs')
+        logsdir = reportdir._str.replace('preproc_report', 'logs')
     elif type(logsdir)==pathlib.PosixPath:
         logsdir = logsdir._str
         
diff --git a/osl/report/src_report.py b/osl/report/src_report.py
index 27c960dc..f6baab5e 100644
--- a/osl/report/src_report.py
+++ b/osl/report/src_report.py
@@ -22,14 +22,14 @@
 from ..source_recon import parcellation
 
 
-def gen_html_data(config, src_dir, subject, reportdir, logger=None, extra_funcs=None, logsdir=None):
+def gen_html_data(config, outdir, subject, reportdir, logger=None, extra_funcs=None, logsdir=None):
     """Generate data for HTML report.
 
     Parameters
     ----------
     config : dict
         Source reconstruction config.
-    src_dir : str
+    outdir : str
         Source reconstruction directory.
     subject : str
         Subject name.
@@ -43,20 +43,13 @@ def gen_html_data(config, src_dir, subject, reportdir, logger=None, extra_funcs=
         Directory the log files were saved into. If None, log files are assumed
         to be in reportdir.replace('report', 'logs')
     """
-    src_dir = Path(src_dir)
+    outdir = Path(outdir)
     reportdir = Path(reportdir)
 
     # Make directory for plots contained in the report
     os.makedirs(reportdir, exist_ok=True)
     os.makedirs(reportdir / subject, exist_ok=True)
 
-    # Open data saved by the source_recon.wrappers
-    data_file = f"{src_dir}/{subject}/report_data.pkl"
-    if Path(data_file).exists():
-        subject_data = pickle.load(open(data_file, "rb"))
-    else:
-        return
-
     # Check if this function has been called before
     if Path(f"{reportdir}/{subject}/data.pkl").exists():
         # Load the data object from last time
@@ -65,12 +58,8 @@ def gen_html_data(config, src_dir, subject, reportdir, logger=None, extra_funcs=
         if "config" in data:
             # Update the config based on this run
             data["config"] = update_config(data["config"], config)
-
-    # Otherwise, this is the first time this has been called
-    else:
-        # Data for the report
-        data = {}
-        data["config"] = config
+        else:
+            data["config"] = config
 
     # add extra funcs if they exist
     if extra_funcs is not None:
@@ -83,54 +72,54 @@ def gen_html_data(config, src_dir, subject, reportdir, logger=None, extra_funcs=
     data["filename"] = subject
 
     # What have we done for this subject?
-    data["compute_surfaces"] = subject_data.pop("compute_surfaces", False)
-    data["coregister"] = subject_data.pop("coregister", False)
-    data["beamform"] = subject_data.pop("beamform", False)
-    data["beamform_and_parcellate"] = subject_data.pop("beamform_and_parcellate", False)
-    data["fix_sign_ambiguity"] = subject_data.pop("fix_sign_ambiguity", False)
+    data["compute_surfaces"] = data.pop("compute_surfaces", False)
+    data["coregister"] = data.pop("coregister", False)
+    data["beamform"] = data.pop("beamform", False)
+    data["beamform_and_parcellate"] = data.pop("beamform_and_parcellate", False)
+    data["fix_sign_ambiguity"] = data.pop("fix_sign_ambiguity", False)
 
     # Save info
     if data["beamform_and_parcellate"]:
-        data["n_samples"] = subject_data["n_samples"]
+        data["n_samples"] = data["n_samples"]
     if data["coregister"]:
-        data["fid_err"] = subject_data["fid_err"]
+        data["fid_err"] = data["fid_err"]
     if data["beamform_and_parcellate"]:
-        data["parcellation_file"] = subject_data["parcellation_file"]
-        data["parcellation_filename"] = Path(subject_data["parcellation_file"]).name
+        data["parcellation_file"] = data["parcellation_file"]
+        data["parcellation_filename"] = Path(data["parcellation_file"]).name
     if data["fix_sign_ambiguity"]:
-        data["template"] = subject_data["template"]
-        data["metrics"] = subject_data["metrics"]
+        data["template"] = data["template"]
+        data["metrics"] = data["metrics"]
 
     # Copy plots
-    if "surface_plots" in subject_data:
-        for plot in subject_data["surface_plots"]:
+    if "surface_plots" in data:
+        for plot in data["surface_plots"]:
             surface = "surfaces_" + Path(plot).stem
             data[f"plt_{surface}"] = f"{subject}/{surface}.png"
-            copy("{}/{}".format(src_dir, plot), "{}/{}/{}.png".format(reportdir, subject, surface))
+            copy("{}/{}".format(outdir, plot), "{}/{}/{}.png".format(reportdir, subject, surface))
 
-    if "coreg_plot" in subject_data:
+    if "coreg_plot" in data:
         data["plt_coreg"] = f"{subject}/coreg.html"
-        copy("{}/{}".format(src_dir, subject_data["coreg_plot"]), "{}/{}/coreg.html".format(reportdir, subject))
+        copy("{}/{}".format(outdir, data["coreg_plot"]), "{}/{}/coreg.html".format(reportdir, subject))
 
-    if "filters_cov_plot" in subject_data:
+    if "filters_cov_plot" in data:
         data["plt_filters_cov"] = f"{subject}/filters_cov.png"
-        copy("{}/{}".format(src_dir, subject_data["filters_cov_plot"]), "{}/{}/filters_cov.png".format(reportdir, subject))
+        copy("{}/{}".format(outdir, data["filters_cov_plot"]), "{}/{}/filters_cov.png".format(reportdir, subject))
 
-    if "filters_svd_plot" in subject_data:
+    if "filters_svd_plot" in data:
         data["plt_filters_svd"] = f"{subject}/filters_svd.png"
-        copy("{}/{}".format(src_dir, subject_data["filters_svd_plot"]), "{}/{}/filters_svd.png".format(reportdir, subject))
+        copy("{}/{}".format(outdir, data["filters_svd_plot"]), "{}/{}/filters_svd.png".format(reportdir, subject))
 
-    if "parc_psd_plot" in subject_data:
+    if "parc_psd_plot" in data:
         data["plt_parc_psd"] = f"{subject}/parc_psd.png"
-        copy("{}/{}".format(src_dir, subject_data["parc_psd_plot"]), "{}/{}/parc_psd.png".format(reportdir, subject))
+        copy("{}/{}".format(outdir, data["parc_psd_plot"]), "{}/{}/parc_psd.png".format(reportdir, subject))
 
-    if "parc_corr_plot" in subject_data:
+    if "parc_corr_plot" in data:
         data["plt_parc_corr"] = f"{subject}/parc_corr.png"
-        copy("{}/{}".format(src_dir, subject_data["parc_corr_plot"]), "{}/{}/parc_corr.png".format(reportdir, subject))
+        copy("{}/{}".format(outdir, data["parc_corr_plot"]), "{}/{}/parc_corr.png".format(reportdir, subject))
 
     # Logs
     if logsdir is None:
-        logsdir = os.path.join(src_dir._str, 'logs')
+        logsdir = os.path.join(outdir, 'logs')
     
     # guess the log file name
     g = glob(os.path.join(logsdir, f'{subject}*.log'))    
@@ -142,7 +131,6 @@ def gen_html_data(config, src_dir, subject, reportdir, logger=None, extra_funcs=
                 else:
                     data['log'] = log_file.read()
 
-            
     # Save data in the report directory
     pickle.dump(data, open(f"{reportdir}/{subject}/data.pkl", "wb"))
 
@@ -293,7 +281,7 @@ def gen_html_summary(reportdir, logsdir=None):
 
     # log files
     if logsdir is None:
-        logsdir = reportdir._str.replace('report', 'logs')
+        logsdir = reportdir._str.replace('src_report', 'logs')
         
     if os.path.exists(os.path.join(logsdir, 'osl_batch.log')):
         with open(os.path.join(logsdir, 'osl_batch.log'), 'r') as log_file:
@@ -466,9 +454,11 @@ def add_to_data(data_file, info):
     info : dict
         Info to add.
     """
-    if Path(data_file).exists():
+    data_file = Path(data_file)
+    if data_file.exists():
         data = pickle.load(open(data_file, "rb"))
     else:
+        data_file.parent.mkdir(parents=True)
         data = {}
     data.update(info)
     pickle.dump(data, open(data_file, "wb"))
diff --git a/osl/source_recon/batch.py b/osl/source_recon/batch.py
index 4ea641c3..8a4ad588 100644
--- a/osl/source_recon/batch.py
+++ b/osl/source_recon/batch.py
@@ -90,7 +90,7 @@ def find_func(method, extra_funcs):
 
 def run_src_chain(
     config,
-    src_dir,
+    outdir,
     subject,
     preproc_file=None,
     smri_file=None,
@@ -108,7 +108,7 @@ def run_src_chain(
     ----------
     config : str or dict
         Source reconstruction config.
-    src_dir : str
+    outdir : str
         Source reconstruction directory.
     subject : str
         Subject name.
@@ -139,15 +139,12 @@ def run_src_chain(
     rhino.fsl_utils.check_fsl()
 
     # Directories
-    src_dir = validate_outdir(src_dir)
-    logsdir = validate_outdir(logsdir or src_dir / "logs")
-    reportdir = validate_outdir(reportdir or src_dir / "report")
+    outdir = validate_outdir(outdir)
+    logsdir = validate_outdir(logsdir or outdir / "logs")
+    reportdir = validate_outdir(reportdir or outdir / "src_report")
 
-    # Get run ID
-    if preproc_file is None:
-        run_id = subject
-    else:
-        run_id = find_run_id(preproc_file)
+    # Use the subject ID for the run ID
+    run_id = subject
 
     # Generate log filename
     name_base = "{run_id}_{ftype}.{fext}"
@@ -161,7 +158,7 @@ def run_src_chain(
     logger = logging.getLogger(__name__)
     now = strftime("%Y-%m-%d %H:%M:%S", localtime())
     logger.info("{0} : Starting OSL Processing".format(now))
-    logger.info("input : {0}".format(src_dir / subject))
+    logger.info("input : {0}".format(outdir / subject))
 
     # Load config
     if not isinstance(config, dict):
@@ -189,7 +186,26 @@ def run_src_chain(
                         + "Please pass via extra_funcs "
                         + f"or use available functions: {avail_names}."
                     )
-            func(src_dir, subject, preproc_file, smri_file, epoch_file, **userargs)
+            def wrapped_func(**kwargs):
+                args, _, _, defaults = inspect.getargspec(func)
+                args_with_defaults = args[-len(defaults):]
+                kwargs_to_pass = {}
+                for a in args:
+                    if a in kwargs:
+                        kwargs_to_pass[a] = kwargs[a]
+                    elif a not in args_with_defaults:
+                        raise ValueError(f"{a} needs to be passed to {func.__name__}")
+                return func(**kwargs_to_pass)
+            wrapped_func(
+                outdir=outdir,
+                subject=subject,
+                preproc_file=preproc_file,
+                smri_file=smri_file,
+                epoch_file=epoch_file,
+                reportdir=reportdir,
+                logsdir=logsdir,
+                **userargs,
+            )
 
     except Exception as e:
         logger.critical("*********************************")
@@ -215,16 +231,15 @@ def run_src_chain(
         return False
 
     if gen_report:
-        # Generate data and individual HTML for the report
-        src_report.gen_html_data(config, src_dir, subject, reportdir, extra_funcs=extra_funcs)
-        src_report.gen_html_page(reportdir)
+        # Generate data and individual HTML data for the report
+        src_report.gen_html_data(config, outdir, subject, reportdir, extra_funcs=extra_funcs)
 
     return True
 
 
 def run_src_batch(
     config,
-    src_dir,
+    outdir,
     subjects,
     preproc_files=None,
     smri_files=None,
@@ -243,7 +258,7 @@ def run_src_batch(
     ----------
     config : str or dict
         Source reconstruction config.
-    src_dir : str
+    outdir : str
         Source reconstruction directory.
     subjects : list of str
         Subject names.
@@ -277,9 +292,9 @@ def run_src_batch(
     rhino.fsl_utils.check_fsl()
 
     # Directories
-    src_dir = validate_outdir(src_dir)
-    logsdir = validate_outdir(logsdir or src_dir / "logs")
-    reportdir = validate_outdir(reportdir or src_dir / "report")
+    outdir = validate_outdir(outdir)
+    logsdir = validate_outdir(logsdir or outdir / "logs")
+    reportdir = validate_outdir(reportdir or outdir / "src_report")
 
     # Initialise Loggers
     mne.set_log_level(mneverbose)
@@ -292,12 +307,50 @@ def run_src_batch(
     config_str = pprint.PrettyPrinter().pformat(config)
     logger.info('Running config\n {0}'.format(config_str))
 
-    # Validation
+    # Number of files (subjects) to process
     n_subjects = len(subjects)
-    if preproc_files is not None:
-        n_preproc_files = len(preproc_files)
-        if n_subjects != n_preproc_files:
-            raise ValueError(f"Got {n_subjects} subjects and {n_preproc_files} preproc_files.")
+
+    # Validation
+    if preproc_files is not None and epoch_files is not None:
+        raise ValueError("Please pass either preproc_file or epoch_files, not both.")
+
+    if preproc_files and epoch_files:
+        raise ValueError(
+            "Cannot pass both preproc_files=True and epoch_files=True. "
+            "Please only pass one of these."
+        )
+
+    if isinstance(preproc_files, list):
+        n_files = len(preproc_files)
+        if n_subjects != n_files:
+            raise ValueError(f"Got {n_subjects} subjects and {n_files} preproc_files.")
+
+    elif isinstance(epoch_files, list):
+        n_files = len(epoch_files)
+        if n_subjects != n_files:
+            raise ValueError(f"Got {n_subjects} subjects and {n_files} epoch_files.")
+
+    else:
+        # Check what files are in the output directory
+        preproc_files_list = []
+        epoch_files_list = []
+        for subject in subjects:
+            preproc_file = f"{outdir}/{subject}/{subject}_preproc-raw.fif"
+            epoch_file = f"{outdir}/{subject}/{subject}-epo.fif"
+            if os.path.exists(preproc_file) and os.path.exists(epoch_file):
+                if preproc_files is None and epoch_files is None:
+                    raise ValueError(
+                        "Both preproc and epoch fif files found. "
+                        "Please pass preproc_files=True or epoch_files=True."
+                    )
+            elif os.path.exists(preproc_file):
+                preproc_files_list.append(preproc_file)
+            elif os.path.exists(epoch_file):
+                epoch_files_list.append(epoch_file)
+        if len(preproc_files_list) > 0:
+            preproc_files = preproc_files_list
+        elif len(epoch_files_list) > 0:
+            epoch_files = epochs_file_list
 
     doing_coreg = (
         any(["compute_surfaces" in method for method in config["source_recon"]]) or
@@ -329,7 +382,7 @@ def run_src_batch(
     # Loop through input files to generate arguments for run_coreg_chain
     args = []
     for subject, preproc_file, smri_file, epoch_file, in zip(subjects, preproc_files, smri_files, epoch_files):
-        args.append((config, src_dir, subject, preproc_file, smri_file, epoch_file))
+        args.append((config, outdir, subject, preproc_file, smri_file, epoch_file))
 
     # Actually run the processes
     if dask_client:
diff --git a/osl/source_recon/beamforming.py b/osl/source_recon/beamforming.py
index e7d2f942..2e2d2a10 100644
--- a/osl/source_recon/beamforming.py
+++ b/osl/source_recon/beamforming.py
@@ -70,7 +70,7 @@ def get_beamforming_filenames(subjects_dir, subject):
     """
     basedir = op.join(subjects_dir, subject, "beamform")
     if " " in basedir:
-        raise ValueError("subjects_dir/src_dir cannot contain spaces.")
+        raise ValueError("subjects_dir cannot contain spaces.")
     os.makedirs(basedir, exist_ok=True)
     
     filenames = {
diff --git a/osl/source_recon/rhino/polhemus.py b/osl/source_recon/rhino/polhemus.py
index f2a19696..d039ae12 100644
--- a/osl/source_recon/rhino/polhemus.py
+++ b/osl/source_recon/rhino/polhemus.py
@@ -310,14 +310,14 @@ def on_press(event):
 
     plt.show()
 
-def remove_stray_headshape_points(src_dir, subject, nose=True):
+def remove_stray_headshape_points(outdir, subject, nose=True):
     """Remove stray headshape points.
 
     Removes headshape points near the nose, on the neck or far away from the head.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to subjects directory.
     subject : str
         Subject directory name.
@@ -326,7 +326,7 @@ def remove_stray_headshape_points(src_dir, subject, nose=True):
         Useful to remove these if we have defaced structurals or aren't
         extracting the nose from the structural.
     """
-    filenames = get_coreg_filenames(src_dir, subject)
+    filenames = get_coreg_filenames(outdir, subject)
 
     # Load saved headshape and nasion files
     hs = np.loadtxt(filenames["polhemus_headshape_file"])
@@ -352,12 +352,12 @@ def remove_stray_headshape_points(src_dir, subject, nose=True):
     np.savetxt(filenames["polhemus_headshape_file"], hs)
 
 
-def extract_polhemus_from_pos(src_dir, subject, filepath):
+def extract_polhemus_from_pos(outdir, subject, filepath):
     """Saves fiducials/headshape from a pos file.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Subjects directory.
     subject : str
         Subject subdirectory/ID.
@@ -369,7 +369,7 @@ def extract_polhemus_from_pos(src_dir, subject, filepath):
     """
 
     # Get coreg filenames
-    filenames = get_coreg_filenames(src_dir, subject)
+    filenames = get_coreg_filenames(outdir, subject)
 
     # Load file
     if "{0}" in filepath:
@@ -405,12 +405,12 @@ def extract_polhemus_from_pos(src_dir, subject, filepath):
     np.savetxt(filenames["polhemus_headshape_file"], polhemus_headshape)
 
 
-def extract_polhemus_from_elc(src_dir, subject, filepath, remove_headshape_near_nose=False):
+def extract_polhemus_from_elc(outdir, subject, filepath, remove_headshape_near_nose=False):
     """Saves fiducials/headshape from an elc file.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Subjects directory.
     subject : str
         Subject subdirectory/ID.
@@ -424,7 +424,7 @@ def extract_polhemus_from_elc(src_dir, subject, filepath, remove_headshape_near_
     """
 
     # Get coreg filenames
-    filenames = get_coreg_filenames(src_dir, subject)
+    filenames = get_coreg_filenames(outdir, subject)
 
     # Load elc file
     if "{0}" in filepath:
diff --git a/osl/source_recon/rhino/utils.py b/osl/source_recon/rhino/utils.py
index 638f4af2..3d51ba6c 100644
--- a/osl/source_recon/rhino/utils.py
+++ b/osl/source_recon/rhino/utils.py
@@ -63,7 +63,7 @@ def get_rhino_files(subjects_dir, subject):
     # Base RHINO directory
     rhino_dir = op.join(subjects_dir, subject, "rhino")
     if " " in rhino_dir:
-        raise ValueError("subjects_dir/src_dir cannot contain spaces.")
+        raise ValueError("subjects_dir cannot contain spaces.")
 
     # Surfaces files
     surfaces_dir = op.join(rhino_dir, "surfaces")
diff --git a/osl/source_recon/sign_flipping.py b/osl/source_recon/sign_flipping.py
index efb8e585..865dfccc 100644
--- a/osl/source_recon/sign_flipping.py
+++ b/osl/source_recon/sign_flipping.py
@@ -291,12 +291,12 @@ def apply_flips_to_covariance(cov, flips, n_embeddings=1):
     return cov * flips
 
 
-def apply_flips(src_dir, subject, flips, epoched=False):
+def apply_flips(outdir, subject, flips, epoched=False):
     """Saves the sign flipped data.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to source reconstruction directory.
     subject : str
         Subject name/id.
@@ -306,7 +306,7 @@ def apply_flips(src_dir, subject, flips, epoched=False):
         Are we performing sign flipping on parc-raw.fif (epoched=False) or parc-epo.fif files (epoched=True)?
     """
     if epoched:
-        parc_file = op.join(src_dir, str(subject), "parc", "parc-epo.fif")
+        parc_file = op.join(outdir, str(subject), "parc", "parc-epo.fif")
         epochs = mne.read_epochs(parc_file, verbose=False)
         sflip_epochs = epochs.copy()
         sflip_epochs.load_data()
@@ -318,13 +318,13 @@ def flip(data):
         sflip_epochs.apply_function(flip, picks=_get_parc_chans(epochs), channel_wise=False)
 
         # Save
-        outfile = op.join(src_dir, str(subject), "sflip_parc-epo.fif")
+        outfile = op.join(outdir, str(subject), str(subject) + "_sflip_parc-epo.fif")
         log_or_print(f"saving: {outfile}")
         sflip_epochs.save(outfile, overwrite=True)
 
     else:
         # Load parcellated data
-        parc_file = op.join(src_dir, str(subject), "parc", "parc-raw.fif")
+        parc_file = op.join(outdir, str(subject), "parc", "parc-raw.fif")
         raw = mne.io.read_raw_fif(parc_file, verbose=False)
         sflip_raw = raw.copy()
         sflip_raw.load_data()
@@ -336,7 +336,7 @@ def flip(data):
         sflip_raw.apply_function(flip, picks=_get_parc_chans(raw), channel_wise=False)
 
         # Save
-        outfile = op.join(src_dir, str(subject), "sflip_parc-raw.fif")
+        outfile = op.join(outdir, str(subject), str(subject) + "_sflip_parc-raw.fif")
         log_or_print(f"saving: {outfile}")
         sflip_raw.save(outfile, overwrite=True)
 
diff --git a/osl/source_recon/wrappers.py b/osl/source_recon/wrappers.py
index 089dbece..44ce5d67 100644
--- a/osl/source_recon/wrappers.py
+++ b/osl/source_recon/wrappers.py
@@ -1,14 +1,7 @@
 """Wrappers for source reconstruction.
 
-This module contains the functions callable using a 'source_recon' section
-of a config.
-
-All functions in this module accept the following arguments for consistency:
-
-    func(src_dir, subject, preproc_file, smri_file, epoch_file, *userargs)
-
-Custom functions (i.e. functions passed via the extra_funcs argument) must
-also conform to this.
+This module contains the functions callable using a 'source_recon'
+section of a config.
 """
 
 # Authors: Chetan Gohil <chetan.gohil@psych.ox.ac.uk>
@@ -34,40 +27,36 @@
 
 
 def extract_polhemus_from_info(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
-    smri_file,
-    epoch_file,
-    **userargs,
+    include_eeg_as_headshape=False,
+    include_hpi_as_headshape=True,
 ):
     """Wrapper function to extract fiducials/headshape points.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
     preproc_file : str
         Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
-    userargs : keyword arguments
-        Keyword arguments to pass to
-        osl.source_recon.rhino.extract_polhemus_from_info.
+    include_eeg_as_headshape : bool, optional
+        Should we include EEG locations as headshape points?
+    include_hpi_as_headshape : bool, optional
+        Should we include HPI locations as headshape points?
     """
-    filenames = rhino.get_coreg_filenames(src_dir, subject)
+    filenames = rhino.get_coreg_filenames(outdir, subject)
     rhino.extract_polhemus_from_info(
         fif_file=preproc_file,
         headshape_outfile=filenames["polhemus_headshape_file"],
         nasion_outfile=filenames["polhemus_nasion_file"],
         rpa_outfile=filenames["polhemus_rpa_file"],
         lpa_outfile=filenames["polhemus_lpa_file"],
-        **userargs,
+        include_eeg_as_headshape=include_eeg_as_headshape,
+        include_hpi_as_headshape=include_hpi_as_headshape,
     )
 
 
@@ -77,62 +66,34 @@ def extract_fiducials_from_fif(*args, **kwargs):
     extract_polhemus_from_info(*args, **kwargs)
 
 
-def remove_stray_headshape_points(
-    src_dir,
-    subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
-    nose=True,
-):
+def remove_stray_headshape_points(outdir, subject, nose=True):
     """Remove stray headshape points.
 
     This function removes headshape points on the nose, neck and far from the head.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file. Not used.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
     noise : bool, optional
         Should we remove headshape points near the nose?
         Useful to remove these if we have defaced structurals or aren't
         extracting the nose from the structural.
     """
-    rhino.remove_stray_headshape_points(src_dir, subject, nose=nose)
+    rhino.remove_stray_headshape_points(outdir, subject, nose=nose)
 
 
-def save_mni_fiducials(
-    src_dir,
-    subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
-    filepath,
-):
+def save_mni_fiducials(outdir, subject, filepath):
     """Wrapper to save MNI fiducials.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file. Not used.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
     filepath : str
         Full path to the text file containing the fiducials.
 
@@ -151,7 +112,7 @@ def save_mni_fiducials(
 
         The order of the coordinates is the same as given in FSLeyes.
     """
-    filenames = rhino.get_coreg_filenames(src_dir, subject)
+    filenames = rhino.get_coreg_filenames(outdir, subject)
     if "{0}" in filepath:
         fiducials_file = filepath.format(subject)
     else:
@@ -164,44 +125,27 @@ def save_mni_fiducials(
     )
 
 
-def extract_polhemus_from_pos(
-    src_dir,
-    subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
-    filepath,
-):
+def extract_polhemus_from_pos(outdir, subject, filepath):
     """Wrapper to save polhemus data from a .pos file.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file. Not used.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
     filepath : str
         Full path to the pos file for this subject.
         Any reference to '{subject}' (or '{0}') is replaced by the subject ID.
         E.g. 'data/{subject}/meg/{subject}_headshape.pos' with subject='sub-001'
         becomes 'data/sub-001/meg/sub-001_headshape.pos'.
     """
-    rhino.extract_polhemus_from_pos(src_dir, subject, filepath)
+    rhino.extract_polhemus_from_pos(outdir, subject, filepath)
 
 
 def extract_polhemus_from_elc(
-    src_dir,
+    outdir,
     subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
     filepath,
     remove_headshape_near_nose=False,
 ):
@@ -209,17 +153,10 @@ def extract_polhemus_from_elc(
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file. Not used.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
     filepath : str
         Full path to the elc file for this subject.
         Any reference to '{subject}' (or '{0}') is replaced by the subject ID.
@@ -229,36 +166,31 @@ def extract_polhemus_from_elc(
         Should we remove any headshape points near the nose?
     """
     rhino.extract_polhemus_from_elc(
-        src_dir, subject, filepath, remove_headshape_near_nose
+        outdir, subject, filepath, remove_headshape_near_nose
     )
 
 
 def compute_surfaces(
-    src_dir,
+    outdir,
     subject,
-    preproc_file,
     smri_file,
-    epoch_file,
     include_nose=True,
     recompute_surfaces=False,
     do_mri2mniaxes_xform=True,
     use_qform=False,
+    reportdir=None,
 ):
     """Wrapper for computing surfaces.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file.
     smri_file : str
         Path to the T1 weighted structural MRI file to use in source
         reconstruction.
-    epoch_file : str
-        Path to epoched preprocessed fif file.
     include_nose : bool, optional
         Should we include the nose when we're extracting the surfaces?
     recompute_surfaces : bool, optional
@@ -271,6 +203,8 @@ def compute_surfaces(
     use_qform : bool, optional
         Should we replace the sform with the qform? Useful if the sform code
         is incompatible with OSL, but the qform is compatible.
+    reportdir : str, optional
+        Path to report directory.
     """
     if smri_file == "standard":
         std_struct = "MNI152_T1_2mm.nii.gz"
@@ -280,7 +214,7 @@ def compute_surfaces(
     # Compute surfaces
     already_computed = rhino.compute_surfaces(
         smri_file=smri_file,
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         include_nose=include_nose,
         recompute_surfaces=recompute_surfaces,
@@ -290,40 +224,41 @@ def compute_surfaces(
 
     # Plot surfaces
     surface_plots = rhino.plot_surfaces(
-        src_dir, subject, include_nose, already_computed
-    )
-    surface_plots = [s.replace(f"{src_dir}/", "") for s in surface_plots]
-
-    # Save info for the report
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "compute_surfaces": True,
-            "include_nose": include_nose,
-            "do_mri2mniaxes_xform": do_mri2mniaxes_xform,
-            "use_qform": use_qform,
-            "surface_plots": surface_plots,
-        },
+        outdir, subject, include_nose, already_computed
     )
+    surface_plots = [s.replace(f"{outdir}/", "") for s in surface_plots]
+
+    if reportdir is not None:
+        # Save info for the report
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "compute_surfaces": True,
+                "include_nose": include_nose,
+                "do_mri2mniaxes_xform": do_mri2mniaxes_xform,
+                "use_qform": use_qform,
+                "surface_plots": surface_plots,
+            },
+        )
 
 
 def coregister(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
     smri_file,
-    epoch_file,
     use_nose=True,
     use_headshape=True,
     already_coregistered=False,
     allow_smri_scaling=False,
     n_init=1,
+    reportdir=None,
 ):
     """Wrapper for coregistration.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
@@ -332,8 +267,6 @@ def coregister(
     smri_file : str
         Path to the T1 weighted structural MRI file to use in source
         reconstruction.
-    epoch_file : str
-        Path to epoched preprocessed fif file.
     use_nose : bool, optional
         Should we use the nose in the coregistration?
     use_headshape : bool, optional
@@ -350,11 +283,13 @@ def coregister(
         using a template sMRI that has not come from this subject.
     n_init : int, optional
         Number of initialisations for coregistration.
+    reportdir : str, optional
+        Path to report directory.
     """
     # Run coregistration
     rhino.coreg(
         fif_file=preproc_file,
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         use_headshape=use_headshape,
         use_nose=use_nose,
@@ -367,59 +302,51 @@ def coregister(
     if already_coregistered:
         fid_err = None
     else:
-        fid_err = rhino.coreg_metrics(subjects_dir=src_dir, subject=subject)
+        fid_err = rhino.coreg_metrics(subjects_dir=outdir, subject=subject)
 
     # Save plots
-    coreg_dir = rhino.get_coreg_filenames(src_dir, subject)["basedir"]
+    coreg_dir = rhino.get_coreg_filenames(outdir, subject)["basedir"]
     rhino.coreg_display(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         display_outskin_with_nose=False,
         filename=f"{coreg_dir}/coreg.html",
     )
-    coreg_filename = f"{coreg_dir}/coreg.html".replace(f"{src_dir}/", "")
-
-    # Save info for the report
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "coregister": True,
-            "use_headshape": use_headshape,
-            "use_nose": use_nose,
-            "already_coregistered": already_coregistered,
-            "allow_smri_scaling": allow_smri_scaling,
-            "n_init_coreg": n_init,
-            "fid_err": fid_err,
-            "coreg_plot": coreg_filename,
-        },
-    )
+    coreg_filename = f"{coreg_dir}/coreg.html".replace(f"{outdir}/", "")
+
+    if reportdir is not None:
+        # Save info for the report
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "coregister": True,
+                "use_headshape": use_headshape,
+                "use_nose": use_nose,
+                "already_coregistered": already_coregistered,
+                "allow_smri_scaling": allow_smri_scaling,
+                "n_init_coreg": n_init,
+                "fid_err": fid_err,
+                "coreg_plot": coreg_filename,
+            },
+        )
 
 
 def forward_model(
-    src_dir,
+    outdir,
     subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
     gridstep=8,
     model="Single Layer",
     eeg=False,
+    reportdir=None,
 ):
     """Wrapper for computing the forward model.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction.
-    epoch_file : str
-        Path to epoched preprocessed fif file.
     gridstep : int, optional
         A grid will be constructed with the spacing given by ``gridstep``
         in mm, generating a volume source space.
@@ -430,26 +357,29 @@ def forward_model(
         'Triple Layer' uses three layers (scalp, inner skull, brain/cortex)
     eeg : bool, optional
         Are we using EEG channels in the source reconstruction?
+    reportdir : str, optional
+        Path to report directory.
     """
     # Compute forward model
     rhino.forward_model(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         model=model,
         gridstep=gridstep,
         eeg=eeg,
     )
 
-    # Save info for the report
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "forward_model": True,
-            "model": model,
-            "gridstep": gridstep,
-            "eeg": eeg,
-        },
-    )
+    if reportdir is not None:
+        # Save info for the report
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "forward_model": True,
+                "model": model,
+                "gridstep": gridstep,
+                "eeg": eeg,
+            },
+        )
 
 
 # -------------------------------------
@@ -457,10 +387,9 @@ def forward_model(
 
 
 def beamform(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
-    smri_file,
     epoch_file,
     chantypes,
     rank,
@@ -468,20 +397,18 @@ def beamform(
     weight_norm="nai",
     pick_ori="max-power-pre-weight-norm",
     reg=0,
+    reportdir=None,
 ):
     """Wrapper function for beamforming.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
     preproc_file : str
         Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction.
     epoch_file : str
         Path to epoched preprocessed fif file.
     chantypes : str or list of str
@@ -498,6 +425,8 @@ def beamform(
         Orientation of the dipoles.
     reg : float, optional
         The regularization for the whitened data covariance.
+    reportdir : str, optional
+        Path to report directory
     """
     logger.info("beamforming")
 
@@ -529,7 +458,7 @@ def beamform(
     logger.info(f"chantypes: {chantypes}")
     logger.info(f"rank: {rank}")
     filters = beamforming.make_lcmv(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         data=data,
         chantypes=chantypes,
@@ -542,31 +471,31 @@ def beamform(
 
     # Make plots
     filters_cov_plot, filters_svd_plot = beamforming.make_plots(
-        src_dir, subject, filters, data
-    )
-    filters_cov_plot = filters_cov_plot.replace(f"{src_dir}/", "")
-    filters_svd_plot = filters_svd_plot.replace(f"{src_dir}/", "")
-
-    # Save info for the report
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "beamform": True,
-            "chantypes": chantypes,
-            "rank": rank,
-            "reg": reg,
-            "freq_range": freq_range,
-            "filters_cov_plot": filters_cov_plot,
-            "filters_svd_plot": filters_svd_plot,
-        },
+        outdir, subject, filters, data
     )
+    filters_cov_plot = filters_cov_plot.replace(f"{outdir}/", "")
+    filters_svd_plot = filters_svd_plot.replace(f"{outdir}/", "")
+
+    if reportdir is not None:
+        # Save info for the report
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "beamform": True,
+                "chantypes": chantypes,
+                "rank": rank,
+                "reg": reg,
+                "freq_range": freq_range,
+                "filters_cov_plot": filters_cov_plot,
+                "filters_svd_plot": filters_svd_plot,
+            },
+        )
 
 
 def parcellate(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
-    smri_file,
     epoch_file,
     parcellation_file,
     method,
@@ -574,20 +503,18 @@ def parcellate(
     spatial_resolution=None,
     reference_brain="mni",
     extra_chans="stim",
+    reportdir=None,
 ):
     """Wrapper function for parcellation.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
     preproc_file : str
         Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction.
     epoch_file : str
         Path to epoched preprocessed fif file.
     parcellation_file : str
@@ -613,11 +540,19 @@ def parcellate(
         Extra channels to include in the parc-raw.fif file.
         Defaults to 'stim'. Stim channels are always added to parc-raw.fif
         in addition to extra_chans.
+    reportdir : str, optional
+        Path to report directory.
     """
     logger.info("parcellate")
 
+    if reportdir is None:
+        raise ValueError(
+            "This function can only be used then a report was generated "
+            "when beamforming. Please use beamform_and_parcellate."
+        )
+
     # Get settings passed to the beamform wrapper
-    report_data = pickle.load(open(f"{src_dir}/{subject}/report_data.pkl", "rb"))
+    report_data = pickle.load(open(f"{reportdir}/{subject}/data.pkl", "rb"))
     freq_range = report_data.pop("freq_range")
     chantypes = report_data.pop("chantypes")
     if isinstance(chantypes, str):
@@ -644,7 +579,7 @@ def parcellate(
     chantype_data = data.copy().pick(chantypes)
 
     # Load beamforming filter and apply
-    filters = beamforming.load_lcmv(src_dir, subject)
+    filters = beamforming.load_lcmv(outdir, subject)
     bf_data = beamforming.apply_lcmv(chantype_data, filters)
 
     if epoch_file is not None:
@@ -652,7 +587,7 @@ def parcellate(
     else:
         bf_data = bf_data.data
     bf_data_mni, _, coords_mni, _ = beamforming.transform_recon_timeseries(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         recon_timeseries=bf_data,
         spatial_resolution=spatial_resolution,
@@ -666,7 +601,7 @@ def parcellate(
         voxel_timeseries=bf_data_mni,
         voxel_coords=coords_mni,
         method=method,
-        working_dir=f"{src_dir}/{subject}/parc",
+        working_dir=f"{outdir}/{subject}/parc",
     )
 
     # Orthogonalisation
@@ -681,7 +616,7 @@ def parcellate(
 
     if epoch_file is None:
         # Save parcellated data as a MNE Raw object
-        parc_fif_file = f"{src_dir}/{subject}/parc/parc-raw.fif"
+        parc_fif_file = f"{outdir}/{subject}/parc/parc-raw.fif"
         logger.info(f"saving {parc_fif_file}")
         parc_raw = parcellation.convert2mne_raw(
             parcel_data, data, extra_chans=extra_chans
@@ -689,7 +624,7 @@ def parcellate(
         parc_raw.save(parc_fif_file, overwrite=True)
     else:
         # Save parcellated data as a MNE Epochs object
-        parc_fif_file = f"{src_dir}/{subject}/parc/parc-epo.fif"
+        parc_fif_file = f"{outdir}/{subject}/parc/parc-epo.fif"
         logger.info(f"saving {parc_fif_file}")
         parc_epo = parcellation.convert2mne_epochs(parcel_data, data)
         parc_epo.save(parc_fif_file, overwrite=True)
@@ -701,10 +636,10 @@ def parcellate(
         fs=data.info["sfreq"],
         freq_range=freq_range,
         parcellation_file=parcellation_file,
-        filename=f"{src_dir}/{parc_psd_plot}",
+        filename=f"{outdir}/{parc_psd_plot}",
     )
     parc_corr_plot = f"{subject}/parc/corr.png"
-    parcellation.plot_correlation(parcel_data, filename=f"{src_dir}/{parc_corr_plot}")
+    parcellation.plot_correlation(parcel_data, filename=f"{outdir}/{parc_corr_plot}")
 
     # Save info for the report
     n_parcels = parcel_data.shape[0]
@@ -714,7 +649,7 @@ def parcellate(
     else:
         n_epochs = None
     src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
+        f"{reportdir}/{subject}/data.pkl",
         {
             "parcellate": True,
             "parcellation_file": parcellation_file,
@@ -731,10 +666,9 @@ def parcellate(
 
 
 def beamform_and_parcellate(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
-    smri_file,
     epoch_file,
     chantypes,
     rank,
@@ -748,20 +682,18 @@ def beamform_and_parcellate(
     spatial_resolution=None,
     reference_brain="mni",
     extra_chans="stim",
+    reportdir=None,
 ):
     """Wrapper function for beamforming and parcellation.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
     preproc_file : str
         Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction.
     epoch_file : str
         Path to epoched preprocessed fif file.
     chantypes : str or list of str
@@ -802,6 +734,8 @@ def beamform_and_parcellate(
         Extra channels to include in the parc-raw.fif file.
         Defaults to 'stim'. Stim channels are always added to parc-raw.fif
         in addition to extra_chans.
+    reportdir : str, optional
+        Path to report directory.
     """
     logger.info("beamform_and_parcellate")
 
@@ -833,7 +767,7 @@ def beamform_and_parcellate(
     logger.info(f"chantypes: {chantypes}")
     logger.info(f"rank: {rank}")
     filters = beamforming.make_lcmv(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         data=data,
         chantypes=chantypes,
@@ -846,10 +780,10 @@ def beamform_and_parcellate(
 
     # Make plots
     filters_cov_plot, filters_svd_plot = beamforming.make_plots(
-        src_dir, subject, filters, chantype_data
+        outdir, subject, filters, chantype_data
     )
-    filters_cov_plot = filters_cov_plot.replace(f"{src_dir}/", "")
-    filters_svd_plot = filters_svd_plot.replace(f"{src_dir}/", "")
+    filters_cov_plot = filters_cov_plot.replace(f"{outdir}/", "")
+    filters_svd_plot = filters_svd_plot.replace(f"{outdir}/", "")
 
     # Apply beamforming
     bf_data = beamforming.apply_lcmv(chantype_data, filters)
@@ -859,7 +793,7 @@ def beamform_and_parcellate(
     else:
         bf_data = bf_data.data
     bf_data_mni, _, coords_mni, _ = beamforming.transform_recon_timeseries(
-        subjects_dir=src_dir,
+        subjects_dir=outdir,
         subject=subject,
         recon_timeseries=bf_data,
         spatial_resolution=spatial_resolution,
@@ -874,7 +808,7 @@ def beamform_and_parcellate(
         voxel_timeseries=bf_data_mni,
         voxel_coords=coords_mni,
         method=method,
-        working_dir=f"{src_dir}/{subject}/parc",
+        working_dir=f"{outdir}/{subject}/parc",
     )
 
     # Orthogonalisation
@@ -889,7 +823,7 @@ def beamform_and_parcellate(
 
     if epoch_file is None:
         # Save parcellated data as a MNE Raw object
-        parc_fif_file = f"{src_dir}/{subject}/parc/parc-raw.fif"
+        parc_fif_file = f"{outdir}/{subject}/parc/parc-raw.fif"
         logger.info(f"saving {parc_fif_file}")
         parc_raw = parcellation.convert2mne_raw(
             parcel_data, data, extra_chans=extra_chans
@@ -897,7 +831,7 @@ def beamform_and_parcellate(
         parc_raw.save(parc_fif_file, overwrite=True)
     else:
         # Save parcellated data as a MNE Epochs object
-        parc_fif_file = f"{src_dir}/{subject}/parc/parc-epo.fif"
+        parc_fif_file = f"{outdir}/{subject}/parc/parc-epo.fif"
         logger.info(f"saving {parc_fif_file}")
         parc_epo = parcellation.convert2mne_epochs(parcel_data, data)
         parc_epo.save(parc_fif_file, overwrite=True)
@@ -909,41 +843,42 @@ def beamform_and_parcellate(
         fs=data.info["sfreq"],
         freq_range=freq_range,
         parcellation_file=parcellation_file,
-        filename=f"{src_dir}/{parc_psd_plot}",
+        filename=f"{outdir}/{parc_psd_plot}",
     )
     parc_corr_plot = f"{subject}/parc/corr.png"
-    parcellation.plot_correlation(parcel_data, filename=f"{src_dir}/{parc_corr_plot}")
-
-    # Save info for the report
-    n_parcels = parcel_data.shape[0]
-    n_samples = parcel_data.shape[1]
-    if parcel_data.ndim == 3:
-        n_epochs = parcel_data.shape[2]
-    else:
-        n_epochs = None
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "beamform_and_parcellate": True,
-            "beamform": True,
-            "parcellate": True,
-            "chantypes": chantypes,
-            "rank": rank,
-            "reg": reg,
-            "freq_range": freq_range,
-            "filters_cov_plot": filters_cov_plot,
-            "filters_svd_plot": filters_svd_plot,
-            "parcellation_file": parcellation_file,
-            "method": method,
-            "orthogonalisation": orthogonalisation,
-            "parc_fif_file": str(parc_fif_file),
-            "n_samples": n_samples,
-            "n_parcels": n_parcels,
-            "n_epochs": n_epochs,
-            "parc_psd_plot": parc_psd_plot,
-            "parc_corr_plot": parc_corr_plot,
-        },
-    )
+    parcellation.plot_correlation(parcel_data, filename=f"{outdir}/{parc_corr_plot}")
+
+    if reportdir is not None:
+        # Save info for the report
+        n_parcels = parcel_data.shape[0]
+        n_samples = parcel_data.shape[1]
+        if parcel_data.ndim == 3:
+            n_epochs = parcel_data.shape[2]
+        else:
+            n_epochs = None
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "beamform_and_parcellate": True,
+                "beamform": True,
+                "parcellate": True,
+                "chantypes": chantypes,
+                "rank": rank,
+                "reg": reg,
+                "freq_range": freq_range,
+                "filters_cov_plot": filters_cov_plot,
+                "filters_svd_plot": filters_svd_plot,
+                "parcellation_file": parcellation_file,
+                "method": method,
+                "orthogonalisation": orthogonalisation,
+                "parc_fif_file": str(parc_fif_file),
+                "n_samples": n_samples,
+                "n_parcels": n_parcels,
+                "n_epochs": n_epochs,
+                "parc_psd_plot": parc_psd_plot,
+                "parc_corr_plot": parc_corr_plot,
+            },
+        )
 
 
 # ----------------------
@@ -951,7 +886,7 @@ def beamform_and_parcellate(
 
 
 def find_template_subject(
-    src_dir,
+    outdir,
     subjects,
     n_embeddings=1,
     standardize=True,
@@ -960,12 +895,12 @@ def find_template_subject(
     """Function to find a good subject to align other subjects to in the sign flipping.
 
     Note, this function expects parcellated data to exist in the following
-    location: src_dir/*/parc/parc-*.fif, the * here represents subject
+    location: outdir/*/parc/parc-*.fif, the * here represents subject
     directories or 'raw' vs 'epo'.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subjects : str
         Subjects to include.
@@ -988,9 +923,9 @@ def find_template_subject(
     parc_files = []
     for subject in subjects:
         if epoched:
-            parc_file = f"{src_dir}/{subject}/parc/parc-epo.fif"
+            parc_file = f"{outdir}/{subject}/parc/parc-epo.fif"
         else:
-            parc_file = f"{src_dir}/{subject}/parc/parc-raw.fif"
+            parc_file = f"{outdir}/{subject}/parc/parc-raw.fif"
         if Path(parc_file).exists():
             parc_files.append(parc_file)
         else:
@@ -1016,11 +951,9 @@ def find_template_subject(
 
 
 def fix_sign_ambiguity(
-    src_dir,
+    outdir,
     subject,
     preproc_file,
-    smri_file,
-    epoch_file,
     template,
     n_embeddings,
     standardize,
@@ -1028,22 +961,18 @@ def fix_sign_ambiguity(
     n_iter,
     max_flips,
     epoched=False,
+    reportdir=None,
 ):
     """Wrapper function for fixing the dipole sign ambiguity.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to where to output the source reconstruction files.
     subject : str
         Subject name/id.
     preproc_file : str
         Path to the preprocessed fif file.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction.
-    epoch_file : str
-        Path to epoched preprocessed fif file.
     template : str
         Template subject.
     n_embeddings : int
@@ -1059,6 +988,8 @@ def fix_sign_ambiguity(
     epoched : bool, optional
         Are we performing sign flipping on parc-raw.fif (epoched=False) or
         parc-epo.fif files (epoched=True)?
+    reportdir : str, optional
+        Path to report directory.
     """
     logger.info("fix_sign_ambiguity")
     logger.info(f"using template: {template}")
@@ -1067,9 +998,9 @@ def fix_sign_ambiguity(
     parc_files = []
     for sub in [subject, template]:
         if epoched:
-            parc_file = f"{src_dir}/{sub}/parc/parc-epo.fif"
+            parc_file = f"{outdir}/{sub}/parc/parc-epo.fif"
         else:
-            parc_file = f"{src_dir}/{sub}/parc/parc-raw.fif"
+            parc_file = f"{outdir}/{sub}/parc/parc-raw.fif"
         if not Path(parc_file).exists():
             raise ValueError(f"{parc_file} not found")
         parc_files.append(parc_file)
@@ -1091,54 +1022,41 @@ def fix_sign_ambiguity(
     )
 
     # Apply flips to the parcellated data
-    sign_flipping.apply_flips(src_dir, subject, flips, epoched=epoched)
-
-    # Save info for the report
-    src_report.add_to_data(
-        f"{src_dir}/{subject}/report_data.pkl",
-        {
-            "fix_sign_ambiguity": True,
-            "template": template,
-            "n_embeddings": n_embeddings,
-            "standardize": standardize,
-            "n_init": n_init,
-            "n_iter": n_iter,
-            "max_flips": max_flips,
-            "metrics": metrics,
-        },
-    )
+    sign_flipping.apply_flips(outdir, subject, flips, epoched=epoched)
+
+    if reportdir is not None:
+        # Save info for the report
+        src_report.add_to_data(
+            f"{reportdir}/{subject}/data.pkl",
+            {
+                "fix_sign_ambiguity": True,
+                "template": template,
+                "n_embeddings": n_embeddings,
+                "standardize": standardize,
+                "n_init": n_init,
+                "n_iter": n_iter,
+                "max_flips": max_flips,
+                "metrics": metrics,
+            },
+        )
 
 
 # --------------
 # Other wrappers
 
 
-def extract_rhino_files(
-    src_dir,
-    subject,
-    preproc_file,
-    smri_file,
-    epoch_file,
-    old_src_dir,
-):
+def extract_rhino_files(outdir, subject, old_outdir):
     """Wrapper function for extracting RHINO files from a previous run.
 
     Parameters
     ----------
-    src_dir : str
+    outdir : str
         Path to the NEW source reconstruction directory.
     subject : str
         Subject name/id.
-    preproc_file : str
-        Path to the preprocessed fif file. Not used.
-    smri_file : str
-        Path to the T1 weighted structural MRI file to use in source
-        reconstruction. Not used.
-    epoch_file : str
-        Path to epoched preprocessed fif file. Not used.
-    old_src_dir : str
+    old_outdir : str
         OLD source reconstruction directory to copy RHINO files to.
     """
     rhino.utils.extract_rhino_files(
-        old_src_dir, src_dir, subjects=subject, gen_report=False
+        old_outdir, outdir, subjects=subject, gen_report=False
     )
diff --git a/osl/utils/file_handling.py b/osl/utils/file_handling.py
index ea810dd4..96bed6ba 100644
--- a/osl/utils/file_handling.py
+++ b/osl/utils/file_handling.py
@@ -84,7 +84,7 @@ def process_file_inputs(inputs):
     if check_paths:
         #infiles = [sanitise_filepath(f) for f in infiles]
         for idx, fif in enumerate(infiles):
-            if fif.endswith('.ds'):
+            if fif.endswith('.ds') or fif.endswith('.mff'):
                 good_files[idx] = int(os.path.isdir(fif))
             else:
                 good_files[idx] = int(os.path.isfile(fif))
@@ -189,6 +189,8 @@ def get_rawdir(files):
 
 
 def add_subdir(file, outdir, run_id=None):
+    """Add sub-directory."""
+
     if not type(outdir) == str:
         outdir = str(outdir)
     if '{' in outdir and '}' in outdir: