From 4793d2b8cc7c0bb3450915ab2dbc175eafe49e18 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 11:16:29 +0100
Subject: [PATCH 01/38] enh: initialise fieldprep

---
 nmriprep/argprep/fieldprep.py | 34 ++++++++++++++++++++++++++++++++++
 1 file changed, 34 insertions(+)
 create mode 100644 nmriprep/argprep/fieldprep.py

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
new file mode 100644
index 0000000..cbac821
--- /dev/null
+++ b/nmriprep/argprep/fieldprep.py
@@ -0,0 +1,34 @@
+import numpy as np
+
+from ..image import convert_nef_to_grey, save_slice
+from ..parser import get_fieldprep_parser
+from ..utils import find_files, parse_kv
+
+
+def fieldprep():
+    args = get_fieldprep_parser().parse_args()
+
+    if args.dark_field:
+        raise NotImplementedError("Dark field processing coming soon...")
+    
+    if args.flat_field:
+        ff_dir = args.flat_field
+        fnames = find_files(ff_dir.glob('*flatfield*.nef'))
+        if len(fnames) < 1:
+            raise FileNotFoundError(
+                f'No flat field files found in {ff_dir.absolute()}'
+            )
+        out_dir = ff_dir.parent / 'preproc' if not args.output else args.output
+        out_dir.mkdir(parents=True, exist_ok=True)
+
+        data = np.stack(
+            [ convert_nef_to_grey(fname) for fname in fnames] ,
+            axis=2,
+        ).mean(axis=2)
+        out_stem = '_'.join(
+            f'{k}-{v}' for k, v
+            in parse_kv(fnames[0]).items()
+            if "flatfield" not in k
+        )
+        save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
+    return

From 0eb98af4efbab0ac899498a35d90c6087948c031 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 11:17:04 +0100
Subject: [PATCH 02/38] enh: add cli options

---
 nmriprep/parser.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index 1a85efb..d4728ab 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -48,6 +48,19 @@ def get_argprep_parser():
     return parser
 
 
+def get_fieldprep_parser():
+    """Build parser object."""
+
+    parser = ArgumentParser(
+        description='Convert dark/flatfield .nef images for processing with argprep',
+        formatter_class=ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument('--flat-field', help='Path to directory containing flat field image', type=Path, nargs='*')
+    parser.add_argument('--dark-field', help='Path to directory containing dark field image', type=Path, nargs='*')
+    parser.add_argument('--output', help='Optionally specify output directory', type=Path, nargs='*')
+    return parser
+
+
 def get_roiextract_parser():
     """Build parser object."""
 

From 800fedc9a4651c36da25cfea3853da0bdc45009f Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 11:18:23 +0100
Subject: [PATCH 03/38] enh: add fieldprep script to pyproject

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 5e6b66c..0d17c58 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,6 +36,7 @@ Homepage = "https://github.com/brainkcl/nmriprep"
 
 [project.scripts]
 argprep = "nmriprep.argprep.argprep:main"
+fieldprep = "nmriprep.argprep.fieldprep:fieldprep"
 roi_extract = "nmriprep.measure:roi_extract"
 
 [tool.hatch.build]

From 630116272ab256fbb00c8cdc7a8b9d89291750c6 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 11:25:12 +0100
Subject: [PATCH 04/38] fix: number of args for fieldprep

---
 nmriprep/parser.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index d4728ab..fcd121b 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -55,9 +55,9 @@ def get_fieldprep_parser():
         description='Convert dark/flatfield .nef images for processing with argprep',
         formatter_class=ArgumentDefaultsHelpFormatter,
     )
-    parser.add_argument('--flat-field', help='Path to directory containing flat field image', type=Path, nargs='*')
-    parser.add_argument('--dark-field', help='Path to directory containing dark field image', type=Path, nargs='*')
-    parser.add_argument('--output', help='Optionally specify output directory', type=Path, nargs='*')
+    parser.add_argument('--flat-field', help='Path to directory containing flat field image', type=Path)
+    parser.add_argument('--dark-field', help='Path to directory containing dark field image', type=Path)
+    parser.add_argument('--output', help='Optionally specify output directory', type=Path)
     return parser
 
 

From 74c6e0845d8169817eabc67aca6bb32bc316248a Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 11:25:49 +0100
Subject: [PATCH 05/38] fix: specify filename stem for parsing

---
 nmriprep/argprep/fieldprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index cbac821..776b1f0 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -27,7 +27,7 @@ def fieldprep():
         ).mean(axis=2)
         out_stem = '_'.join(
             f'{k}-{v}' for k, v
-            in parse_kv(fnames[0]).items()
+            in parse_kv(fnames[0].stem).items()
             if "flatfield" not in k
         )
         save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )

From d1460837220f4fdc88cf0c209a1582f4afcc1692 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 12:01:37 +0100
Subject: [PATCH 06/38] enh: use kv in name for output

---
 nmriprep/argprep/fieldprep.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 776b1f0..f34f6b7 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -18,17 +18,19 @@ def fieldprep():
             raise FileNotFoundError(
                 f'No flat field files found in {ff_dir.absolute()}'
             )
-        out_dir = ff_dir.parent / 'preproc' if not args.output else args.output
+
+        fname_parts = parse_kv(fnames[0].stem)
+        out_stem = '_'.join(
+            f'{k}-{v}' for k, v
+            in fname_parts.items()
+            if "flatfield" not in k
+        )
+        out_dir = ff_dir.parents[1] / 'preproc' / f"sub-{fname_parts['sub']}" if not args.output else args.output
         out_dir.mkdir(parents=True, exist_ok=True)
 
         data = np.stack(
             [ convert_nef_to_grey(fname) for fname in fnames] ,
             axis=2,
         ).mean(axis=2)
-        out_stem = '_'.join(
-            f'{k}-{v}' for k, v
-            in parse_kv(fnames[0].stem).items()
-            if "flatfield" not in k
-        )
         save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
     return

From 434e46d76a09b50bf55618344be869b094771b3d Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 12:02:05 +0100
Subject: [PATCH 07/38] fix: change mean to median

---
 nmriprep/argprep/fieldprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index f34f6b7..0c4b1b7 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -31,6 +31,6 @@ def fieldprep():
         data = np.stack(
             [ convert_nef_to_grey(fname) for fname in fnames] ,
             axis=2,
-        ).mean(axis=2)
+        ).median(axis=2)
         save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
     return

From 88dcb76bade46e2b6b7162ecb27ddf310468c14f Mon Sep 17 00:00:00 2001
From: Eilidh MacNicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 12:10:12 +0100
Subject: [PATCH 08/38] sty: ruff

---
 nmriprep/argprep/fieldprep.py | 22 +++++++++++-----------
 nmriprep/parser.py            | 12 +++++++++---
 2 files changed, 20 insertions(+), 14 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 0c4b1b7..4a750bf 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -9,28 +9,28 @@ def fieldprep():
     args = get_fieldprep_parser().parse_args()
 
     if args.dark_field:
-        raise NotImplementedError("Dark field processing coming soon...")
-    
+        raise NotImplementedError('Dark field processing coming soon...')
+
     if args.flat_field:
         ff_dir = args.flat_field
         fnames = find_files(ff_dir.glob('*flatfield*.nef'))
         if len(fnames) < 1:
-            raise FileNotFoundError(
-                f'No flat field files found in {ff_dir.absolute()}'
-            )
+            raise FileNotFoundError(f'No flat field files found in {ff_dir.absolute()}')
 
         fname_parts = parse_kv(fnames[0].stem)
         out_stem = '_'.join(
-            f'{k}-{v}' for k, v
-            in fname_parts.items()
-            if "flatfield" not in k
+            f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
+        )
+        out_dir = (
+            ff_dir.parents[1] / 'preproc' / f'sub-{fname_parts["sub"]}'
+            if not args.output
+            else args.output
         )
-        out_dir = ff_dir.parents[1] / 'preproc' / f"sub-{fname_parts['sub']}" if not args.output else args.output
         out_dir.mkdir(parents=True, exist_ok=True)
 
         data = np.stack(
-            [ convert_nef_to_grey(fname) for fname in fnames] ,
+            [convert_nef_to_grey(fname) for fname in fnames],
             axis=2,
         ).median(axis=2)
-        save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
+        save_slice(data, out_dir / f'{out_stem}_flatfield.tif')
     return
diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index fcd121b..05075ad 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -55,9 +55,15 @@ def get_fieldprep_parser():
         description='Convert dark/flatfield .nef images for processing with argprep',
         formatter_class=ArgumentDefaultsHelpFormatter,
     )
-    parser.add_argument('--flat-field', help='Path to directory containing flat field image', type=Path)
-    parser.add_argument('--dark-field', help='Path to directory containing dark field image', type=Path)
-    parser.add_argument('--output', help='Optionally specify output directory', type=Path)
+    parser.add_argument(
+        '--flat-field', help='Path to directory containing flat field image', type=Path
+    )
+    parser.add_argument(
+        '--dark-field', help='Path to directory containing dark field image', type=Path
+    )
+    parser.add_argument(
+        '--output', help='Optionally specify output directory', type=Path
+    )
     return parser
 
 

From 1b2a52f0944a53dcc140289c108d10cc87276632 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:12:19 +0100
Subject: [PATCH 09/38] Revert "fix: change mean to median"

This reverts commit 434e46d76a09b50bf55618344be869b094771b3d.
---
 nmriprep/argprep/fieldprep.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 4a750bf..8b094df 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -31,6 +31,6 @@ def fieldprep():
         data = np.stack(
             [convert_nef_to_grey(fname) for fname in fnames],
             axis=2,
-        ).median(axis=2)
-        save_slice(data, out_dir / f'{out_stem}_flatfield.tif')
+        ).mean(axis=2)
+        save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
     return

From d1a5599064ad358476832834935bf0b598f167e6 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:13:48 +0100
Subject: [PATCH 10/38] fix: change from mean to median

---
 nmriprep/argprep/fieldprep.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 8b094df..4a1d4af 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -28,9 +28,12 @@ def fieldprep():
         )
         out_dir.mkdir(parents=True, exist_ok=True)
 
-        data = np.stack(
-            [convert_nef_to_grey(fname) for fname in fnames],
+        data = np.median(
+            np.stack(
+                [convert_nef_to_grey(fname) for fname in fnames],
+                axis=2,
+            ),
             axis=2,
-        ).mean(axis=2)
+        )
         save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
     return

From e961d88f6359935a91806ab9d3ba91698a71a9dc Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:24:26 +0100
Subject: [PATCH 11/38] sty: ruff

---
 nmriprep/argprep/fieldprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 4a1d4af..74c09dc 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -35,5 +35,5 @@ def fieldprep():
             ),
             axis=2,
         )
-        save_slice(data, out_dir / f"{out_stem}_flatfield.tif" )
+        save_slice(data, out_dir / f'{out_stem}_flatfield.tif')
     return

From c0024194b5fcb80aa965777334d52188f3cdc563 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:56:08 +0100
Subject: [PATCH 12/38] enh: add recursive grouping

---
 nmriprep/argprep/fieldprep.py | 39 ++++++++++++++++++++---------------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 74c09dc..f1e645f 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -1,4 +1,6 @@
 import numpy as np
+from collections import defaultdict
+from pathlib import Path
 
 from ..image import convert_nef_to_grey, save_slice
 from ..parser import get_fieldprep_parser
@@ -16,24 +18,27 @@ def fieldprep():
         fnames = find_files(ff_dir.glob('*flatfield*.nef'))
         if len(fnames) < 1:
             raise FileNotFoundError(f'No flat field files found in {ff_dir.absolute()}')
+        
+        subdirs = defaultdict(list)
+        [subdirs[p.parent].append(p) for p in fnames]
 
-        fname_parts = parse_kv(fnames[0].stem)
-        out_stem = '_'.join(
-            f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
-        )
-        out_dir = (
-            ff_dir.parents[1] / 'preproc' / f'sub-{fname_parts["sub"]}'
-            if not args.output
-            else args.output
-        )
-        out_dir.mkdir(parents=True, exist_ok=True)
+        for subdir in subdirs.keys():
+            sub_files = subdirs[subdir]
+            fname_parts = parse_kv(sub_files[0].stem)
+            out_stem = '_'.join(
+                f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
+            )
+            out_dir = Path(
+                subdir.str.lower().replace('sourcedata', 'preproc')
+            ) if not args.output else args.output
+            out_dir.mkdir(parents=True, exist_ok=True)
 
-        data = np.median(
-            np.stack(
-                [convert_nef_to_grey(fname) for fname in fnames],
+            data = np.median(
+                np.stack(
+                    [convert_nef_to_grey(fname) for fname in sub_files],
+                    axis=2,
+                ),
                 axis=2,
-            ),
-            axis=2,
-        )
-        save_slice(data, out_dir / f'{out_stem}_flatfield.tif')
+            )
+            save_slice(data, out_dir / f'{out_stem}_flatfield.tif')
     return

From 21d45e2feea0dd5b6f1f77b6638161f10bc3af16 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:58:02 +0100
Subject: [PATCH 13/38] fix: add recursive glob

---
 nmriprep/argprep/fieldprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index f1e645f..5285d8b 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -15,7 +15,7 @@ def fieldprep():
 
     if args.flat_field:
         ff_dir = args.flat_field
-        fnames = find_files(ff_dir.glob('*flatfield*.nef'))
+        fnames = find_files(ff_dir.rglob('*flatfield*.nef'))
         if len(fnames) < 1:
             raise FileNotFoundError(f'No flat field files found in {ff_dir.absolute()}')
         

From 7bfca3a00f22d37dd38a2889151f891d31bf8d6e Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 13:58:33 +0100
Subject: [PATCH 14/38] fix: explicit subdir string conversion

---
 nmriprep/argprep/fieldprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 5285d8b..9610f58 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -29,7 +29,7 @@ def fieldprep():
                 f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
             )
             out_dir = Path(
-                subdir.str.lower().replace('sourcedata', 'preproc')
+                str(subdir).lower().replace('sourcedata', 'preproc')
             ) if not args.output else args.output
             out_dir.mkdir(parents=True, exist_ok=True)
 

From 8e7cd28f6212fbfae00a5a03e8e89b11fdfc5e98 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 14:18:41 +0100
Subject: [PATCH 15/38] bug: changing whole path to lower

---
 nmriprep/argprep/fieldprep.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 9610f58..8650beb 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -29,8 +29,8 @@ def fieldprep():
                 f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
             )
             out_dir = Path(
-                str(subdir).lower().replace('sourcedata', 'preproc')
-            ) if not args.output else args.output
+                str(subdir).replace('sourcedata', 'preproc')
+            ).resolve() if not args.output else args.output
             out_dir.mkdir(parents=True, exist_ok=True)
 
             data = np.median(

From c30a9ee83f001308a869279a94fcd08cb39e55a9 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 15:05:02 +0100
Subject: [PATCH 16/38] ref: allow flatfield and darkfield to be specified
 separately

---
 nmriprep/argprep/argprep.py   | 21 +++++++--------------
 nmriprep/argprep/fieldprep.py |  8 +++++++-
 2 files changed, 14 insertions(+), 15 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 8967d67..6c671e9 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -1,11 +1,12 @@
 import nibabel as nb
 import numpy as np
 
-from ..image import convert_nef_to_grey, read_tiff, save_slice
+from ..image import convert_nef_to_grey, save_slice
 from ..parser import get_argprep_parser
 from ..plotting import plot_curve, plot_mosaic, plot_single_slice
 from ..utils import find_files, inverse_rodbard, rodbard
 from .calibration import calibrate_standard
+from .fieldprep import find_fields
 
 
 def main():
@@ -16,19 +17,11 @@ def main():
 
     # attempt to find flat field info
     flatfield_correction = {}
-    if args.dark_field and args.flat_field:
-        flatfield_correction['dark'] = read_tiff(args.dark_field)
-        flatfield_correction['flat'] = read_tiff(args.flat_field)
-    else:
-        # try searching for a preprocessed darkfield
-        latest_ff = find_files(out_dir.glob('*flatfield.tiff'))
-        latest_df = find_files(out_dir.glob('*darkfield.tiff'))
-        if latest_ff and latest_df:
-            flatfield_correction['dark'] = read_tiff(latest_df[-1])
-            flatfield_correction['flat'] = read_tiff(latest_ff[-1])
-        else:
-            print('Skipping flat field correction...')
-            flatfield_correction = None
+    flatfield_correction['dark'] = find_fields(args.dark_field, out_dir.glob('*darkfield.tif*'))
+    flatfield_correction['flat'] = find_fields(args.flat_field, out_dir.glob('*flatfield.tif*'))
+    if not all(flatfield_correction.values()):
+        print('Skipping flat field correction...')
+        flatfield_correction = None
 
     # identify subjects for pipeline
     all_subject_ids = set(
diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index 8650beb..e2652fe 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -2,11 +2,17 @@
 from collections import defaultdict
 from pathlib import Path
 
-from ..image import convert_nef_to_grey, save_slice
+from ..image import convert_nef_to_grey, read_tiff, save_slice
 from ..parser import get_fieldprep_parser
 from ..utils import find_files, parse_kv
 
 
+def find_fields(user=None, search_map=None):
+    fieldpath = user if user is not None else find_files(search_map)[-1]
+    field = read_tiff(fieldpath) if fieldpath else None
+    return field
+
+
 def fieldprep():
     args = get_fieldprep_parser().parse_args()
 

From cffa1c71ef386fde92b4b7074eb95cbc32bdbfcd Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 15:07:13 +0100
Subject: [PATCH 17/38] ref: allow flatfield specification on a subjectwise
 basis

---
 nmriprep/argprep/argprep.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 6c671e9..f6fe46b 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -15,14 +15,6 @@ def main():
     out_dir = src_dir.parent / 'preproc' if not args.output else args.output
     verbose = args.save_intermediate
 
-    # attempt to find flat field info
-    flatfield_correction = {}
-    flatfield_correction['dark'] = find_fields(args.dark_field, out_dir.glob('*darkfield.tif*'))
-    flatfield_correction['flat'] = find_fields(args.flat_field, out_dir.glob('*flatfield.tif*'))
-    if not all(flatfield_correction.values()):
-        print('Skipping flat field correction...')
-        flatfield_correction = None
-
     # identify subjects for pipeline
     all_subject_ids = set(
         [
@@ -48,6 +40,14 @@ def main():
         fig_dir = sub_dir / 'figures'
         fig_dir.mkdir(exist_ok=True)
 
+        # attempt to find flat field info
+        flatfield_correction = {}
+        flatfield_correction['dark'] = find_fields(args.dark_field, sub_dir.glob('*darkfield.tif*'))
+        flatfield_correction['flat'] = find_fields(args.flat_field, sub_dir.glob('*flatfield.tif*'))
+        if not all(flatfield_correction.values()):
+            print('Skipping flat field correction...')
+            flatfield_correction = None
+
         # calibrate standards to transform GV to radioactivity
         popt, std_rad, std_gv, std_stem = calibrate_standard(
             sub_id,

From 5a669f61308e1db29b0f2ee1c475c83e7d7b125f Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 15:09:51 +0100
Subject: [PATCH 18/38] sty: ruff

---
 nmriprep/argprep/argprep.py   |  8 ++++++--
 nmriprep/argprep/fieldprep.py | 13 ++++++++-----
 2 files changed, 14 insertions(+), 7 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index f6fe46b..4d01b49 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -42,8 +42,12 @@ def main():
 
         # attempt to find flat field info
         flatfield_correction = {}
-        flatfield_correction['dark'] = find_fields(args.dark_field, sub_dir.glob('*darkfield.tif*'))
-        flatfield_correction['flat'] = find_fields(args.flat_field, sub_dir.glob('*flatfield.tif*'))
+        flatfield_correction['dark'] = find_fields(
+            args.dark_field, sub_dir.glob('*darkfield.tif*')
+        )
+        flatfield_correction['flat'] = find_fields(
+            args.flat_field, sub_dir.glob('*flatfield.tif*')
+        )
         if not all(flatfield_correction.values()):
             print('Skipping flat field correction...')
             flatfield_correction = None
diff --git a/nmriprep/argprep/fieldprep.py b/nmriprep/argprep/fieldprep.py
index e2652fe..b305e36 100644
--- a/nmriprep/argprep/fieldprep.py
+++ b/nmriprep/argprep/fieldprep.py
@@ -1,7 +1,8 @@
-import numpy as np
 from collections import defaultdict
 from pathlib import Path
 
+import numpy as np
+
 from ..image import convert_nef_to_grey, read_tiff, save_slice
 from ..parser import get_fieldprep_parser
 from ..utils import find_files, parse_kv
@@ -24,7 +25,7 @@ def fieldprep():
         fnames = find_files(ff_dir.rglob('*flatfield*.nef'))
         if len(fnames) < 1:
             raise FileNotFoundError(f'No flat field files found in {ff_dir.absolute()}')
-        
+
         subdirs = defaultdict(list)
         [subdirs[p.parent].append(p) for p in fnames]
 
@@ -34,9 +35,11 @@ def fieldprep():
             out_stem = '_'.join(
                 f'{k}-{v}' for k, v in fname_parts.items() if 'flatfield' not in k
             )
-            out_dir = Path(
-                str(subdir).replace('sourcedata', 'preproc')
-            ).resolve() if not args.output else args.output
+            out_dir = (
+                Path(str(subdir).replace('sourcedata', 'preproc')).resolve()
+                if not args.output
+                else args.output
+            )
             out_dir.mkdir(parents=True, exist_ok=True)
 
             data = np.median(

From b3995124e1dc1b47f771f206d1f5f0cfdd87f6d2 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:42:35 +0100
Subject: [PATCH 19/38] fix: boolean dict value checking

---
 nmriprep/argprep/argprep.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 4d01b49..18aed96 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -48,7 +48,7 @@ def main():
         flatfield_correction['flat'] = find_fields(
             args.flat_field, sub_dir.glob('*flatfield.tif*')
         )
-        if not all(flatfield_correction.values()):
+        if any(v is None for v in flatfield_correction.values()):
             print('Skipping flat field correction...')
             flatfield_correction = None
 

From 65960e759a63f4a09f28a02e5f678880a3be8122 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:47:22 +0100
Subject: [PATCH 20/38] ref: modularise subject workflow

---
 nmriprep/argprep/argprep.py | 251 ++++++++++++++++++------------------
 1 file changed, 127 insertions(+), 124 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 18aed96..d399ef2 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -8,6 +8,132 @@
 from .calibration import calibrate_standard
 from .fieldprep import find_fields
 
+def subject_workflow(sub_id, src_dir, out_dir, args, verbose):
+    sub_dir = out_dir / sub_id
+    sub_dir.mkdir(exist_ok=True, parents=True)
+    fig_dir = sub_dir / 'figures'
+    fig_dir.mkdir(exist_ok=True)
+
+    # attempt to find flat field info
+    flatfield_correction = {}
+    flatfield_correction['dark'] = find_fields(
+        args.dark_field, sub_dir.glob('*darkfield.tif*')
+    )
+    flatfield_correction['flat'] = find_fields(
+        args.flat_field, sub_dir.glob('*flatfield.tif*')
+    )
+    if any(v is None for v in flatfield_correction.values()):
+        print('Skipping flat field correction...')
+        flatfield_correction = None
+
+    # calibrate standards to transform GV to radioactivity
+    popt, std_rad, std_gv, std_stem = calibrate_standard(
+        sub_id,
+        src_dir,
+        args.standard_type,
+        flatfield_correction=flatfield_correction,
+        out_dir=sub_dir if verbose else None,
+    )
+
+    if verbose:
+        plot_curve(std_rad, std_gv, rodbard(std_rad, *popt), sub_dir, std_stem)
+
+    print(f'success! fitting data with parameters: {popt}')
+
+    # find subject files
+    slide_files = find_files(src_dir.glob(f'*subj-{sub_id}*slide*.nef'))
+    if len(slide_files) < 1:
+        raise FileNotFoundError(f'No slide files found for {sub_id} in {src_dir}')
+
+    # convert nefs to grey value
+    data_gv = np.stack(
+        [
+            convert_nef_to_grey(
+                fname,
+                flatfield_correction=flatfield_correction,
+                crop_row=args.crop_height,
+                crop_col=args.crop_width,
+                invert=True,
+            )
+            for fname in slide_files
+        ],
+        axis=2,
+    )
+
+    if args.rotate > 0:
+        data_gv = np.rot90(data_gv, k=args.rotate, axes=(0, 1))
+
+    # calibrate slice data
+    print('Converting slide data to radioactivity')
+    data_radioactivity = inverse_rodbard(data_gv, *popt)
+    # clip "negative" values
+    data_radioactivity[np.isnan(data_radioactivity)] = 0
+    print('Success! Generating output...')
+
+    out_stem = std_stem.split('_standard')[0]
+
+    if args.save_nii:
+        # write out nii image (e.g. for Jim)
+        # find information on number of slides from last file name
+        last_section_parts = slide_files[-1].stem.split('_')
+        max_slide = int(
+            [
+                last_section_parts[idx].split('-')[-1]
+                for idx, val in enumerate(last_section_parts)
+                if 'slide' in val
+            ][0]
+        )
+
+        # iterate through slides and collect sections to concatenate
+        for slide_no in range(max_slide):
+            slide_val = str(slide_no + 1).zfill(2)
+            slide_sections = {
+                fname: idx
+                for idx, fname in enumerate(slide_files)
+                if f'slide-{str(slide_val).zfill(2)}' in str(fname.stem)
+            }
+
+            nb.Nifti1Image(
+                data_radioactivity[..., sorted(slide_sections.values())],
+                affine=None,
+            ).to_filename(
+                sub_dir / f'{out_stem}_slide-{slide_val}_desc-preproc_ARG.nii.gz'
+            )
+
+    if args.save_tif:
+        print('Saving individual files...')
+        for idx, fname in enumerate(slide_files):
+            print(f'{fname.stem}')
+            save_slice(
+                data_radioactivity[..., idx],
+                sub_dir / f'{fname.stem}_desc-preproc_ARG.tif',
+            )
+
+            if verbose:
+                # plot image
+                plot_single_slice(
+                    data_radioactivity[..., idx],
+                    fig_dir / f'{fname.stem}_desc-preproc_ARG.png',
+                )
+
+                # plot fits
+                plot_curve(
+                    std_rad=std_rad,
+                    std_gv=std_gv,
+                    fitted_gv=rodbard(std_rad, *popt),
+                    out_dir=fig_dir,
+                    out_stem=fname.stem,
+                    data_rad=data_radioactivity[..., idx].ravel(),
+                    data_gv=data_gv[..., idx].ravel(),
+                )
+    if args.mosaic_slices:
+        sliced = (
+            data_radioactivity
+            if -1 in args.mosaic_slices
+            else data_radioactivity[..., args.mosaic_slices]
+        )
+        plot_mosaic(sliced, out_dir / f'{out_stem}_desc-preproc_ARG.png')
+
 
 def main():
     args = get_argprep_parser().parse_args()
@@ -35,130 +161,7 @@ def main():
         subjects_to_process = all_subject_ids
 
     for sub_id in subjects_to_process:
-        sub_dir = out_dir / sub_id
-        sub_dir.mkdir(exist_ok=True, parents=True)
-        fig_dir = sub_dir / 'figures'
-        fig_dir.mkdir(exist_ok=True)
-
-        # attempt to find flat field info
-        flatfield_correction = {}
-        flatfield_correction['dark'] = find_fields(
-            args.dark_field, sub_dir.glob('*darkfield.tif*')
-        )
-        flatfield_correction['flat'] = find_fields(
-            args.flat_field, sub_dir.glob('*flatfield.tif*')
-        )
-        if any(v is None for v in flatfield_correction.values()):
-            print('Skipping flat field correction...')
-            flatfield_correction = None
-
-        # calibrate standards to transform GV to radioactivity
-        popt, std_rad, std_gv, std_stem = calibrate_standard(
-            sub_id,
-            src_dir,
-            args.standard_type,
-            flatfield_correction=flatfield_correction,
-            out_dir=sub_dir if verbose else None,
-        )
-
-        if verbose:
-            plot_curve(std_rad, std_gv, rodbard(std_rad, *popt), sub_dir, std_stem)
-
-        print(f'success! fitting data with parameters: {popt}')
-
-        # find subject files
-        slide_files = find_files(src_dir.glob(f'*subj-{sub_id}*slide*.nef'))
-        if len(slide_files) < 1:
-            raise FileNotFoundError(f'No slide files found for {sub_id} in {src_dir}')
-
-        # convert nefs to grey value
-        data_gv = np.stack(
-            [
-                convert_nef_to_grey(
-                    fname,
-                    flatfield_correction=flatfield_correction,
-                    crop_row=args.crop_height,
-                    crop_col=args.crop_width,
-                    invert=True,
-                )
-                for fname in slide_files
-            ],
-            axis=2,
-        )
-
-        if args.rotate > 0:
-            data_gv = np.rot90(data_gv, k=args.rotate, axes=(0, 1))
-
-        # calibrate slice data
-        print('Converting slide data to radioactivity')
-        data_radioactivity = inverse_rodbard(data_gv, *popt)
-        # clip "negative" values
-        data_radioactivity[np.isnan(data_radioactivity)] = 0
-        print('Success! Generating output...')
-
-        out_stem = std_stem.split('_standard')[0]
-
-        if args.save_nii:
-            # write out nii image (e.g. for Jim)
-            # find information on number of slides from last file name
-            last_section_parts = slide_files[-1].stem.split('_')
-            max_slide = int(
-                [
-                    last_section_parts[idx].split('-')[-1]
-                    for idx, val in enumerate(last_section_parts)
-                    if 'slide' in val
-                ][0]
-            )
-
-            # iterate through slides and collect sections to concatenate
-            for slide_no in range(max_slide):
-                slide_val = str(slide_no + 1).zfill(2)
-                slide_sections = {
-                    fname: idx
-                    for idx, fname in enumerate(slide_files)
-                    if f'slide-{str(slide_val).zfill(2)}' in str(fname.stem)
-                }
-
-                nb.Nifti1Image(
-                    data_radioactivity[..., sorted(slide_sections.values())],
-                    affine=None,
-                ).to_filename(
-                    sub_dir / f'{out_stem}_slide-{slide_val}_desc-preproc_ARG.nii.gz'
-                )
-
-        if args.save_tif:
-            print('Saving individual files...')
-            for idx, fname in enumerate(slide_files):
-                print(f'{fname.stem}')
-                save_slice(
-                    data_radioactivity[..., idx],
-                    sub_dir / f'{fname.stem}_desc-preproc_ARG.tif',
-                )
-
-                if verbose:
-                    # plot image
-                    plot_single_slice(
-                        data_radioactivity[..., idx],
-                        fig_dir / f'{fname.stem}_desc-preproc_ARG.png',
-                    )
-
-                    # plot fits
-                    plot_curve(
-                        std_rad=std_rad,
-                        std_gv=std_gv,
-                        fitted_gv=rodbard(std_rad, *popt),
-                        out_dir=fig_dir,
-                        out_stem=fname.stem,
-                        data_rad=data_radioactivity[..., idx].ravel(),
-                        data_gv=data_gv[..., idx].ravel(),
-                    )
-        if args.mosaic_slices:
-            sliced = (
-                data_radioactivity
-                if -1 in args.mosaic_slices
-                else data_radioactivity[..., args.mosaic_slices]
-            )
-            plot_mosaic(sliced, out_dir / f'{out_stem}_desc-preproc_ARG.png')
+        subject_workflow(sub_id, src_dir, out_dir, args, verbose)
 
 
 if __name__ == '__main__':

From ac1bf258b2733af9a7b87a45a81e345f9f55bb81 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:49:33 +0100
Subject: [PATCH 21/38] ref: assume src/sub/data hierarchy and group according
 to sub

---
 nmriprep/argprep/argprep.py | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index d399ef2..7c8ff7b 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -1,3 +1,4 @@
+from collections import defaultdict
 import nibabel as nb
 import numpy as np
 
@@ -142,14 +143,10 @@ def main():
     verbose = args.save_intermediate
 
     # identify subjects for pipeline
-    all_subject_ids = set(
-        [
-            part.split('-')[1]
-            for fpath in src_dir.glob('*.nef')
-            for part in fpath.stem.split('_')
-            if 'subj' in part
-        ]
-    )
+    fnames = find_files(src_dir.rglob('*.nef'))
+    subdirs = defaultdict(list)
+    [subdirs[p.parent].append(p) for p in fnames]
+    all_subject_ids = set([subdir.stem for subdir in subdirs.keys()])
 
     if args.subject_id:
         print(f'Processing subjects: {args.subject_id}')

From f4a8ab23f775fa23ceed4caa7bd23ede86cdee71 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:54:32 +0100
Subject: [PATCH 22/38] ref: add previously found files rather than searching
 each time

---
 nmriprep/argprep/argprep.py     | 22 ++++++++++++++--------
 nmriprep/argprep/calibration.py |  3 +--
 2 files changed, 15 insertions(+), 10 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 7c8ff7b..0748938 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -9,7 +9,8 @@
 from .calibration import calibrate_standard
 from .fieldprep import find_fields
 
-def subject_workflow(sub_id, src_dir, out_dir, args, verbose):
+def subject_workflow(sub_files, out_dir, args, verbose):
+    sub_id = sub_files[0].parent.stem
     sub_dir = out_dir / sub_id
     sub_dir.mkdir(exist_ok=True, parents=True)
     fig_dir = sub_dir / 'figures'
@@ -28,9 +29,12 @@ def subject_workflow(sub_id, src_dir, out_dir, args, verbose):
         flatfield_correction = None
 
     # calibrate standards to transform GV to radioactivity
+    std_files = [fname for fname in sub_files if "standard" in fname.stem]
+    if len(std_files) < 1:
+        raise FileNotFoundError(f'No standard files found for {sub_id}')
     popt, std_rad, std_gv, std_stem = calibrate_standard(
         sub_id,
-        src_dir,
+        std_files,
         args.standard_type,
         flatfield_correction=flatfield_correction,
         out_dir=sub_dir if verbose else None,
@@ -42,9 +46,9 @@ def subject_workflow(sub_id, src_dir, out_dir, args, verbose):
     print(f'success! fitting data with parameters: {popt}')
 
     # find subject files
-    slide_files = find_files(src_dir.glob(f'*subj-{sub_id}*slide*.nef'))
+    slide_files = [fname for fname in sub_files if "slide" in fname.stem]
     if len(slide_files) < 1:
-        raise FileNotFoundError(f'No slide files found for {sub_id} in {src_dir}')
+        raise FileNotFoundError(f'No slide files found for {sub_id}')
 
     # convert nefs to grey value
     data_gv = np.stack(
@@ -146,19 +150,21 @@ def main():
     fnames = find_files(src_dir.rglob('*.nef'))
     subdirs = defaultdict(list)
     [subdirs[p.parent].append(p) for p in fnames]
-    all_subject_ids = set([subdir.stem for subdir in subdirs.keys()])
+    all_subject_directories = [subdir for subdir in subdirs.keys()]
 
     if args.subject_id:
         print(f'Processing subjects: {args.subject_id}')
         subjects_to_process = [
-            subj for subj in all_subject_ids if subj in args.subject_id
+            subj for subj in all_subject_directories
+            if subj.stem.replace("sub-","") in args.subject_id
         ]
     else:
         print('Processing all subjects')
-        subjects_to_process = all_subject_ids
+        subjects_to_process = all_subject_directories
 
     for sub_id in subjects_to_process:
-        subject_workflow(sub_id, src_dir, out_dir, args, verbose)
+        sub_files = subdirs[sub_id]
+        subject_workflow(sub_files, out_dir, args, verbose)
 
 
 if __name__ == '__main__':
diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index cfa73df..5d3eeb1 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -100,7 +100,7 @@ def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=N
 
 
 def calibrate_standard(
-    sub_id, src_dir, standard_type, flatfield_correction=None, out_dir=None
+    standard_files, standard_type, flatfield_correction=None, out_dir=None
 ):
     from scipy.optimize import curve_fit
 
@@ -110,7 +110,6 @@ def calibrate_standard(
     with importlib.resources.open_text(data, 'standards.json') as f:
         standard_vals = pd.read_json(f)[standard_type].dropna()
 
-    standard_files = find_files(src_dir.glob(f'*subj-{sub_id}*standard*.nef'))
     assert len(standard_files) == len(standard_vals)
 
     standards_df = pd.DataFrame(

From a5b27b2a2a5d33b5d0d0582302596d57ed4010b7 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:58:56 +0100
Subject: [PATCH 23/38] ref: standard stem definition using parse_kv

---
 nmriprep/argprep/argprep.py     |  6 ++----
 nmriprep/argprep/calibration.py | 10 +++++++---
 2 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 0748938..c23d453 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -75,8 +75,6 @@ def subject_workflow(sub_files, out_dir, args, verbose):
     data_radioactivity[np.isnan(data_radioactivity)] = 0
     print('Success! Generating output...')
 
-    out_stem = std_stem.split('_standard')[0]
-
     if args.save_nii:
         # write out nii image (e.g. for Jim)
         # find information on number of slides from last file name
@@ -102,7 +100,7 @@ def subject_workflow(sub_files, out_dir, args, verbose):
                 data_radioactivity[..., sorted(slide_sections.values())],
                 affine=None,
             ).to_filename(
-                sub_dir / f'{out_stem}_slide-{slide_val}_desc-preproc_ARG.nii.gz'
+                sub_dir / f'{std_stem}_slide-{slide_val}_desc-preproc_ARG.nii.gz'
             )
 
     if args.save_tif:
@@ -137,7 +135,7 @@ def subject_workflow(sub_files, out_dir, args, verbose):
             if -1 in args.mosaic_slices
             else data_radioactivity[..., args.mosaic_slices]
         )
-        plot_mosaic(sliced, out_dir / f'{out_stem}_desc-preproc_ARG.png')
+        plot_mosaic(sliced, out_dir / f'{std_stem}_desc-preproc_ARG.png')
 
 
 def main():
diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 5d3eeb1..0dc13b4 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -6,7 +6,7 @@
 
 from ..image import convert_nef_to_grey
 from ..plotting import plot_roi
-from ..utils import find_files, rodbard
+from ..utils import parse_kv, rodbard
 
 
 def get_image_patch(center_coord, square_apothem: int = 100):
@@ -111,6 +111,11 @@ def calibrate_standard(
         standard_vals = pd.read_json(f)[standard_type].dropna()
 
     assert len(standard_files) == len(standard_vals)
+    out_stem = '_'.join(
+        f'{k}-{v}' for k, v
+        in parse_kv(standard_files[0]).items()
+        if 'standard' not in k
+    )
 
     standards_df = pd.DataFrame(
         {
@@ -141,7 +146,7 @@ def calibrate_standard(
     X = standards_df['radioactivity (uCi/g)']
     y = standards_df['median grey']
     # https://www.myassays.com/four-parameter-logistic-regression.html
-    print(f'fitting Rodbard curve for {standard_files[0].stem[:-3]}')
+    print(f'fitting Rodbard curve for {out_stem}')
     popt, _ = curve_fit(
         rodbard,
         X,
@@ -152,7 +157,6 @@ def calibrate_standard(
     )
 
     # save for calibrating slice images
-    out_stem = standard_files[0].stem[:-3]
     if out_dir:
         standards_df.to_json(f'{out_dir / out_stem}_standards.json')
         with (out_dir / f'{out_stem}_calibration.json').open(mode='w') as f:

From 315eb9fc5d81b035c9b60989c1e53959e8946143 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 16:59:59 +0100
Subject: [PATCH 24/38] sty: inconsistent path definiton

---
 nmriprep/argprep/calibration.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 0dc13b4..dd53d43 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -158,7 +158,7 @@ def calibrate_standard(
 
     # save for calibrating slice images
     if out_dir:
-        standards_df.to_json(f'{out_dir / out_stem}_standards.json')
+        standards_df.to_json(out_dir / f'{out_stem}_standards.json')
         with (out_dir / f'{out_stem}_calibration.json').open(mode='w') as f:
             json.dump(dict(zip(['min', 'slope', 'ED50', 'max'], popt)), f)
     return popt, X, y, out_stem

From 929d3481631af69bc839026aade3c048b3599b0c Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 17:38:07 +0100
Subject: [PATCH 25/38] fix: remove sub_id from calibrate_standard call

---
 nmriprep/argprep/argprep.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index c23d453..1d8a97f 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -33,7 +33,6 @@ def subject_workflow(sub_files, out_dir, args, verbose):
     if len(std_files) < 1:
         raise FileNotFoundError(f'No standard files found for {sub_id}')
     popt, std_rad, std_gv, std_stem = calibrate_standard(
-        sub_id,
         std_files,
         args.standard_type,
         flatfield_correction=flatfield_correction,

From 9b06a61b91e644c2d2a246d54bdf8fe9772616f6 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Thu, 17 Apr 2025 17:40:19 +0100
Subject: [PATCH 26/38] fix: pass parse_kv str

---
 nmriprep/argprep/calibration.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index dd53d43..b2777af 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -113,7 +113,7 @@ def calibrate_standard(
     assert len(standard_files) == len(standard_vals)
     out_stem = '_'.join(
         f'{k}-{v}' for k, v
-        in parse_kv(standard_files[0]).items()
+        in parse_kv(standard_files[0].stem).items()
         if 'standard' not in k
     )
 

From 89b6af9f600b3032d20df7b544cda74be92ba217 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 22 Apr 2025 14:04:41 +0100
Subject: [PATCH 27/38] ref: rely on dataset_description.json for isotope

---
 nmriprep/argprep/argprep.py     |  6 ++---
 nmriprep/argprep/calibration.py | 14 +++++++++--
 nmriprep/data/standards.json    | 41 ++++++++++++++++++++++++++++++++-
 3 files changed, 55 insertions(+), 6 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 1d8a97f..c7704d7 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -9,7 +9,7 @@
 from .calibration import calibrate_standard
 from .fieldprep import find_fields
 
-def subject_workflow(sub_files, out_dir, args, verbose):
+def subject_workflow(sub_files, src_dir, out_dir, args, verbose):
     sub_id = sub_files[0].parent.stem
     sub_dir = out_dir / sub_id
     sub_dir.mkdir(exist_ok=True, parents=True)
@@ -34,7 +34,7 @@ def subject_workflow(sub_files, out_dir, args, verbose):
         raise FileNotFoundError(f'No standard files found for {sub_id}')
     popt, std_rad, std_gv, std_stem = calibrate_standard(
         std_files,
-        args.standard_type,
+        src_dir,
         flatfield_correction=flatfield_correction,
         out_dir=sub_dir if verbose else None,
     )
@@ -161,7 +161,7 @@ def main():
 
     for sub_id in subjects_to_process:
         sub_files = subdirs[sub_id]
-        subject_workflow(sub_files, out_dir, args, verbose)
+        subject_workflow(sub_files, src_dir, out_dir, args, verbose)
 
 
 if __name__ == '__main__':
diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index b2777af..26cebd6 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -13,6 +13,15 @@ def get_image_patch(center_coord, square_apothem: int = 100):
     return slice(center_coord - square_apothem, center_coord + square_apothem)
 
 
+def get_dataset_standard(source_dir):
+    if not (source_dir / 'dataset_description.json').exists():
+        raise FileNotFoundError(f"Dataset description file missing from {source_dir.resolve()}")
+    with (source_dir / 'dataset_description.json').open('r') as fname:
+        standard_info = json.load(fname)['standard']
+        range_type = standard_info['range'] if 'range' in standard_info.keys().lower() else 'default'
+    return (standard_info['isotope'], range_type)
+
+
 def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=None):
     import statistics
 
@@ -100,15 +109,16 @@ def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=N
 
 
 def calibrate_standard(
-    standard_files, standard_type, flatfield_correction=None, out_dir=None
+    standard_files, src_dir, flatfield_correction=None, out_dir=None
 ):
     from scipy.optimize import curve_fit
 
     from .. import data
 
     # load standard information
+    isotope, range_type = get_dataset_standard(src_dir)
     with importlib.resources.open_text(data, 'standards.json') as f:
-        standard_vals = pd.read_json(f)[standard_type].dropna()
+        standard_vals = pd.Series(json.load(f)[isotope][range_type])
 
     assert len(standard_files) == len(standard_vals)
     out_stem = '_'.join(
diff --git a/nmriprep/data/standards.json b/nmriprep/data/standards.json
index 7c10819..99b8449 100644
--- a/nmriprep/data/standards.json
+++ b/nmriprep/data/standards.json
@@ -1 +1,40 @@
-{"C14": {"background": 0.0, "1": 39.0, "2": 78.0, "3": 159.0, "4": 292.0, "5": 446.0, "6": 656.0, "7": 869.0, "8": 1098.0}, "H3": {"background": 0.0, "1": 2.0, "2": 3.7, "3": 8.0, "4": 16.6, "5": 36.6, "6": 63.1, "7": 138.1, "8": 243.1, "9": 489.1}}
\ No newline at end of file
+{
+    "C14": {
+        "default": {
+            "background": 0.0,
+            "1": 39.0,
+            "2": 78.0,
+            "3": 159.0,
+            "4": 292.0,
+            "5": 446.0,
+            "6": 656.0,
+            "7": 869.0,
+            "8": 1098.0
+        }
+    },
+    "H3": {
+        "wide" : {
+            "background": 0.0,
+            "1": 2.0,
+            "2": 3.7,
+            "3": 8.0,
+            "4": 16.6,
+            "5": 36.6,
+            "6": 63.1,
+            "7": 138.1,
+            "8": 243.1,
+            "9": 489.1
+        },
+        "narrow" : {
+            "background": 0.0,
+            "1": 3.0,
+            "2": 4.7,
+            "3": 8.7,
+            "4": 23.6,
+            "5": 33.5,
+            "6": 40.2,
+            "7": 66.7,
+            "8": 109.4
+        }
+    }
+}
\ No newline at end of file

From 260fafe892c731ec9bc7a30856b3f99ce79d8852 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 22 Apr 2025 14:05:05 +0100
Subject: [PATCH 28/38] chore: remove isotope option from cli

---
 nmriprep/parser.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index 05075ad..ea00851 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -9,9 +9,6 @@ def get_argprep_parser():
         description='Convert .nef image to .nii with uCi/g voxels',
         formatter_class=ArgumentDefaultsHelpFormatter,
     )
-    parser.add_argument(
-        'standard_type', help='radioisotope of standards', choices=['H3', 'C14']
-    )
     parser.add_argument('source_directory', help='raw data directory', type=Path)
     parser.add_argument('--flat-field', help='Path to flat field image', type=Path)
     parser.add_argument('--dark-field', help='Path to dark field image', type=Path)

From c8ea20bae5c6c7f83380745a9cd4e7ef26a29507 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 22 Apr 2025 14:18:13 +0100
Subject: [PATCH 29/38] ref: search for standard images in  function

---
 nmriprep/argprep/argprep.py     |  5 +----
 nmriprep/argprep/calibration.py | 11 +++++++++--
 2 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index c7704d7..ff30830 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -29,11 +29,8 @@ def subject_workflow(sub_files, src_dir, out_dir, args, verbose):
         flatfield_correction = None
 
     # calibrate standards to transform GV to radioactivity
-    std_files = [fname for fname in sub_files if "standard" in fname.stem]
-    if len(std_files) < 1:
-        raise FileNotFoundError(f'No standard files found for {sub_id}')
     popt, std_rad, std_gv, std_stem = calibrate_standard(
-        std_files,
+        sub_files,
         src_dir,
         flatfield_correction=flatfield_correction,
         out_dir=sub_dir if verbose else None,
diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 26cebd6..723592a 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -109,7 +109,7 @@ def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=N
 
 
 def calibrate_standard(
-    standard_files, src_dir, flatfield_correction=None, out_dir=None
+    sub_files, src_dir, flatfield_correction=None, out_dir=None
 ):
     from scipy.optimize import curve_fit
 
@@ -120,7 +120,14 @@ def calibrate_standard(
     with importlib.resources.open_text(data, 'standards.json') as f:
         standard_vals = pd.Series(json.load(f)[isotope][range_type])
 
-    assert len(standard_files) == len(standard_vals)
+    standard_files = [fname for fname in sub_files if f"standard-{isotope}" in fname.stem]
+    if len(standard_files) < 1:
+        raise FileNotFoundError(f'No {isotope} standard files found in {sub_files[0].parent}')
+    if len(standard_files) != len(standard_vals):
+        # try filtering standard files by range type in case there are two sets of standard images
+        standard_files = [fname for fname in standard_files if f"range-{range_type}" in fname.stem]
+        if len(standard_files) != len(standard_vals):
+            raise RuntimeError(f"Number of standard files {len(standard_files)} does not match standard values")
     out_stem = '_'.join(
         f'{k}-{v}' for k, v
         in parse_kv(standard_files[0].stem).items()

From 5ae0520924e25a9a1fcfda1be32a26a72a58f48a Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 22 Apr 2025 17:41:24 +0100
Subject: [PATCH 30/38] fix: assume standard keys is lower

---
 nmriprep/argprep/calibration.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 723592a..4ef165a 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -18,7 +18,7 @@ def get_dataset_standard(source_dir):
         raise FileNotFoundError(f"Dataset description file missing from {source_dir.resolve()}")
     with (source_dir / 'dataset_description.json').open('r') as fname:
         standard_info = json.load(fname)['standard']
-        range_type = standard_info['range'] if 'range' in standard_info.keys().lower() else 'default'
+        range_type = standard_info['range'] if 'range' in standard_info.keys() else 'default'
     return (standard_info['isotope'], range_type)
 
 

From 51202ed834d37c6b5e6ff89495f10f6d1a5ad961 Mon Sep 17 00:00:00 2001
From: eugenegkim <53093555+eugenegkim@users.noreply.github.com>
Date: Wed, 23 Apr 2025 09:36:50 +0100
Subject: [PATCH 31/38] fix: boolean logic in auto standard detection

---
 nmriprep/argprep/calibration.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 4ef165a..2d9e5a0 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -57,7 +57,7 @@ def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=N
         for peak1, peak2 in zip(peak_loc[:-1], peak_loc[1:]):
             troughs = trough_loc[np.logical_and(trough_loc > peak1, trough_loc < peak2)]
             thresholds.append(
-                min(troughs) if troughs else statistics.mean([peak1, peak2])
+                min(troughs) if len(troughs) > 0 else statistics.mean([peak1, peak2])
             )
             regions = np.digitize(gray_medfilt, bins=thresholds)
 

From dc5039223409df848d0ad2c3818edefb037492c8 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Fri, 9 May 2025 11:29:21 +0100
Subject: [PATCH 32/38] fix: subj typo

---
 nmriprep/utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nmriprep/utils.py b/nmriprep/utils.py
index d85af53..0218b52 100644
--- a/nmriprep/utils.py
+++ b/nmriprep/utils.py
@@ -70,12 +70,12 @@ def inverse_rodbard(y, min_, slope, ed50, max_):
 
 def normalise_by_region(df, region):
     region_df = df.query((f'region == "{region}"'))
-    if region_df.duplicated(['subj', 'slide', 'section']).any():
+    if region_df.duplicated(['sub', 'slide', 'section']).any():
         raise ValueError('region_df has duplicate keys!')
     region_df[f'median_{region}_values'] = df['values'].apply(np.median)
     out = df.merge(
         region_df,
-        on=['subj', 'slide', 'section'],
+        on=['sub', 'slide', 'section'],
         how='left',
         suffixes=('', '_r'),
         validate='m:1',

From 49a85305072a946f1e63b5538241bd92eaab0537 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Fri, 9 May 2025 11:36:52 +0100
Subject: [PATCH 33/38] enh: flexibility to change normalisation summary
 statistic at command line

---
 nmriprep/measure.py | 2 +-
 nmriprep/parser.py  | 7 +++++++
 nmriprep/utils.py   | 6 +++---
 3 files changed, 11 insertions(+), 4 deletions(-)

diff --git a/nmriprep/measure.py b/nmriprep/measure.py
index 19cd2b5..7f1421e 100644
--- a/nmriprep/measure.py
+++ b/nmriprep/measure.py
@@ -62,7 +62,7 @@ def roi_extract():
             merge_keys = [col for col in summary_df.columns if 'values' not in col]
             for region in args.norm_regions:
                 array_col = f'{region}_values'
-                main_df[array_col] = normalise_by_region(main_df, region)
+                main_df[array_col] = normalise_by_region(main_df, region, measure=args.norm_measure)
                 summary_df = summary_df.merge(
                     summarise_vals(
                         main_df[merge_keys + [array_col]],
diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index ea00851..3ced723 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -91,6 +91,13 @@ def get_roiextract_parser():
         nargs='*',
         type=str,
     )
+    parser.add_argument(
+        '--norm-measure',
+        help='summary statistic for normalisation',
+        choices=['mean', 'median', 'mode'],
+        default='median',
+        type=str,
+    )
     parser.add_argument(
         '--output', help='name of output .json file', default='roi_values', type=str
     )
diff --git a/nmriprep/utils.py b/nmriprep/utils.py
index 0218b52..393a71a 100644
--- a/nmriprep/utils.py
+++ b/nmriprep/utils.py
@@ -68,11 +68,11 @@ def inverse_rodbard(y, min_, slope, ed50, max_):
     return ed50 * (((min_ - max_) / (y - max_)) - 1.0) ** (1.0 / slope)
 
 
-def normalise_by_region(df, region):
+def normalise_by_region(df, region, measure='median'):
     region_df = df.query((f'region == "{region}"'))
     if region_df.duplicated(['sub', 'slide', 'section']).any():
         raise ValueError('region_df has duplicate keys!')
-    region_df[f'median_{region}_values'] = df['values'].apply(np.median)
+    region_df[f'{measure}_{region}_values'] = df['values'].apply(np.median)
     out = df.merge(
         region_df,
         on=['sub', 'slide', 'section'],
@@ -80,4 +80,4 @@ def normalise_by_region(df, region):
         suffixes=('', '_r'),
         validate='m:1',
     )
-    return out['values'] / out[f'median_{region}_values']
+    return out['values'] / out[f'{measure}_{region}_values']

From b1244b285fe35a85eb863b4f59a4ecdceb00d680 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 10 Jun 2025 11:42:04 +0100
Subject: [PATCH 34/38] enh: include normalisation modality

---
 nmriprep/utils.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/nmriprep/utils.py b/nmriprep/utils.py
index 393a71a..0f89974 100644
--- a/nmriprep/utils.py
+++ b/nmriprep/utils.py
@@ -69,10 +69,11 @@ def inverse_rodbard(y, min_, slope, ed50, max_):
 
 
 def normalise_by_region(df, region, measure='median'):
+    summary_measure = {'mean': np.mean, 'median': np.median}[measure]
     region_df = df.query((f'region == "{region}"'))
     if region_df.duplicated(['sub', 'slide', 'section']).any():
         raise ValueError('region_df has duplicate keys!')
-    region_df[f'{measure}_{region}_values'] = df['values'].apply(np.median)
+    region_df[f'{measure}_{region}_values'] = df['values'].apply(summary_measure)
     out = df.merge(
         region_df,
         on=['sub', 'slide', 'section'],

From 80ca06f2c15d431125c8601c36b31e6cd4dbeaaf Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 10 Jun 2025 11:42:27 +0100
Subject: [PATCH 35/38] bug: drop mode from parser

---
 nmriprep/parser.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nmriprep/parser.py b/nmriprep/parser.py
index 3ced723..4a32f81 100644
--- a/nmriprep/parser.py
+++ b/nmriprep/parser.py
@@ -94,7 +94,7 @@ def get_roiextract_parser():
     parser.add_argument(
         '--norm-measure',
         help='summary statistic for normalisation',
-        choices=['mean', 'median', 'mode'],
+        choices=['mean', 'median'],
         default='median',
         type=str,
     )

From f550cf84689db71e0a5f99c10dca19e4cf8f8f16 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Tue, 10 Jun 2025 13:49:40 +0100
Subject: [PATCH 36/38] enh: add logic to separate subject images by film

---
 nmriprep/argprep/argprep.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index ff30830..943f7e2 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -5,7 +5,7 @@
 from ..image import convert_nef_to_grey, save_slice
 from ..parser import get_argprep_parser
 from ..plotting import plot_curve, plot_mosaic, plot_single_slice
-from ..utils import find_files, inverse_rodbard, rodbard
+from ..utils import find_files, inverse_rodbard, rodbard, parse_kv
 from .calibration import calibrate_standard
 from .fieldprep import find_fields
 
@@ -158,7 +158,13 @@ def main():
 
     for sub_id in subjects_to_process:
         sub_files = subdirs[sub_id]
-        subject_workflow(sub_files, src_dir, out_dir, args, verbose)
+        if "film" in sub_files[0].stem:
+            subfilms = defaultdict(list)
+            [ subfilms[parse_kv(fname.stem)['film']].append(fname) for fname in sub_files ]
+            for film_idx in subfilms.keys():
+                subject_workflow(subfilms[film_idx], src_dir, out_dir, args, verbose)
+        else:
+            subject_workflow(sub_files, src_dir, out_dir, args, verbose)
 
 
 if __name__ == '__main__':

From 6d4f863f9f37df42fea335af67d12a76b7832c5f Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Wed, 23 Jul 2025 15:56:56 +0100
Subject: [PATCH 37/38] fix: allow lateralised regions for normalisation

---
 nmriprep/utils.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/nmriprep/utils.py b/nmriprep/utils.py
index 0f89974..17fcb3f 100644
--- a/nmriprep/utils.py
+++ b/nmriprep/utils.py
@@ -72,7 +72,15 @@ def normalise_by_region(df, region, measure='median'):
     summary_measure = {'mean': np.mean, 'median': np.median}[measure]
     region_df = df.query((f'region == "{region}"'))
     if region_df.duplicated(['sub', 'slide', 'section']).any():
-        raise ValueError('region_df has duplicate keys!')
+        # hemisphere duplicates are allowed, but those are the only exception
+        if not region_df.duplicated(['sub', 'slide', 'section', 'hemi']).any():
+            region_df = (
+                region_df
+                .groupby(['sub', 'slide', 'section'], as_index=False)
+                .agg({'values': lambda arrs: np.concatenate(arrs.values)})
+            )
+        else:
+            raise ValueError('region_df has duplicate keys!')
     region_df[f'{measure}_{region}_values'] = df['values'].apply(summary_measure)
     out = df.merge(
         region_df,

From f6335df2bc4cec35ae1bfc626c4e12cf4dcceb83 Mon Sep 17 00:00:00 2001
From: eilidhmacnicol <eilidhmacnicol@gmail.com>
Date: Wed, 23 Jul 2025 15:59:22 +0100
Subject: [PATCH 38/38] sty: ruff

---
 nmriprep/argprep/argprep.py     | 18 ++++++++++++------
 nmriprep/argprep/calibration.py | 32 +++++++++++++++++++++-----------
 nmriprep/measure.py             |  4 +++-
 nmriprep/utils.py               |  8 +++-----
 4 files changed, 39 insertions(+), 23 deletions(-)

diff --git a/nmriprep/argprep/argprep.py b/nmriprep/argprep/argprep.py
index 943f7e2..5cf57a9 100644
--- a/nmriprep/argprep/argprep.py
+++ b/nmriprep/argprep/argprep.py
@@ -1,14 +1,16 @@
 from collections import defaultdict
+
 import nibabel as nb
 import numpy as np
 
 from ..image import convert_nef_to_grey, save_slice
 from ..parser import get_argprep_parser
 from ..plotting import plot_curve, plot_mosaic, plot_single_slice
-from ..utils import find_files, inverse_rodbard, rodbard, parse_kv
+from ..utils import find_files, inverse_rodbard, parse_kv, rodbard
 from .calibration import calibrate_standard
 from .fieldprep import find_fields
 
+
 def subject_workflow(sub_files, src_dir, out_dir, args, verbose):
     sub_id = sub_files[0].parent.stem
     sub_dir = out_dir / sub_id
@@ -42,7 +44,7 @@ def subject_workflow(sub_files, src_dir, out_dir, args, verbose):
     print(f'success! fitting data with parameters: {popt}')
 
     # find subject files
-    slide_files = [fname for fname in sub_files if "slide" in fname.stem]
+    slide_files = [fname for fname in sub_files if 'slide' in fname.stem]
     if len(slide_files) < 1:
         raise FileNotFoundError(f'No slide files found for {sub_id}')
 
@@ -149,8 +151,9 @@ def main():
     if args.subject_id:
         print(f'Processing subjects: {args.subject_id}')
         subjects_to_process = [
-            subj for subj in all_subject_directories
-            if subj.stem.replace("sub-","") in args.subject_id
+            subj
+            for subj in all_subject_directories
+            if subj.stem.replace('sub-', '') in args.subject_id
         ]
     else:
         print('Processing all subjects')
@@ -158,9 +161,12 @@ def main():
 
     for sub_id in subjects_to_process:
         sub_files = subdirs[sub_id]
-        if "film" in sub_files[0].stem:
+        if 'film' in sub_files[0].stem:
             subfilms = defaultdict(list)
-            [ subfilms[parse_kv(fname.stem)['film']].append(fname) for fname in sub_files ]
+            [
+                subfilms[parse_kv(fname.stem)['film']].append(fname)
+                for fname in sub_files
+            ]
             for film_idx in subfilms.keys():
                 subject_workflow(subfilms[film_idx], src_dir, out_dir, args, verbose)
         else:
diff --git a/nmriprep/argprep/calibration.py b/nmriprep/argprep/calibration.py
index 2d9e5a0..b4cf042 100644
--- a/nmriprep/argprep/calibration.py
+++ b/nmriprep/argprep/calibration.py
@@ -15,10 +15,14 @@ def get_image_patch(center_coord, square_apothem: int = 100):
 
 def get_dataset_standard(source_dir):
     if not (source_dir / 'dataset_description.json').exists():
-        raise FileNotFoundError(f"Dataset description file missing from {source_dir.resolve()}")
+        raise FileNotFoundError(
+            f'Dataset description file missing from {source_dir.resolve()}'
+        )
     with (source_dir / 'dataset_description.json').open('r') as fname:
         standard_info = json.load(fname)['standard']
-        range_type = standard_info['range'] if 'range' in standard_info.keys() else 'default'
+        range_type = (
+            standard_info['range'] if 'range' in standard_info.keys() else 'default'
+        )
     return (standard_info['isotope'], range_type)
 
 
@@ -108,9 +112,7 @@ def get_standard_value(array, medfilt_radius=40, square_size=900, roi_fig_name=N
     return np.median(gray[roi])
 
 
-def calibrate_standard(
-    sub_files, src_dir, flatfield_correction=None, out_dir=None
-):
+def calibrate_standard(sub_files, src_dir, flatfield_correction=None, out_dir=None):
     from scipy.optimize import curve_fit
 
     from .. import data
@@ -120,17 +122,25 @@ def calibrate_standard(
     with importlib.resources.open_text(data, 'standards.json') as f:
         standard_vals = pd.Series(json.load(f)[isotope][range_type])
 
-    standard_files = [fname for fname in sub_files if f"standard-{isotope}" in fname.stem]
+    standard_files = [
+        fname for fname in sub_files if f'standard-{isotope}' in fname.stem
+    ]
     if len(standard_files) < 1:
-        raise FileNotFoundError(f'No {isotope} standard files found in {sub_files[0].parent}')
+        raise FileNotFoundError(
+            f'No {isotope} standard files found in {sub_files[0].parent}'
+        )
     if len(standard_files) != len(standard_vals):
         # try filtering standard files by range type in case there are two sets of standard images
-        standard_files = [fname for fname in standard_files if f"range-{range_type}" in fname.stem]
+        standard_files = [
+            fname for fname in standard_files if f'range-{range_type}' in fname.stem
+        ]
         if len(standard_files) != len(standard_vals):
-            raise RuntimeError(f"Number of standard files {len(standard_files)} does not match standard values")
+            raise RuntimeError(
+                f'Number of standard files {len(standard_files)} does not match standard values'
+            )
     out_stem = '_'.join(
-        f'{k}-{v}' for k, v
-        in parse_kv(standard_files[0].stem).items()
+        f'{k}-{v}'
+        for k, v in parse_kv(standard_files[0].stem).items()
         if 'standard' not in k
     )
 
diff --git a/nmriprep/measure.py b/nmriprep/measure.py
index 7f1421e..2b034ad 100644
--- a/nmriprep/measure.py
+++ b/nmriprep/measure.py
@@ -62,7 +62,9 @@ def roi_extract():
             merge_keys = [col for col in summary_df.columns if 'values' not in col]
             for region in args.norm_regions:
                 array_col = f'{region}_values'
-                main_df[array_col] = normalise_by_region(main_df, region, measure=args.norm_measure)
+                main_df[array_col] = normalise_by_region(
+                    main_df, region, measure=args.norm_measure
+                )
                 summary_df = summary_df.merge(
                     summarise_vals(
                         main_df[merge_keys + [array_col]],
diff --git a/nmriprep/utils.py b/nmriprep/utils.py
index 17fcb3f..4d5308b 100644
--- a/nmriprep/utils.py
+++ b/nmriprep/utils.py
@@ -74,11 +74,9 @@ def normalise_by_region(df, region, measure='median'):
     if region_df.duplicated(['sub', 'slide', 'section']).any():
         # hemisphere duplicates are allowed, but those are the only exception
         if not region_df.duplicated(['sub', 'slide', 'section', 'hemi']).any():
-            region_df = (
-                region_df
-                .groupby(['sub', 'slide', 'section'], as_index=False)
-                .agg({'values': lambda arrs: np.concatenate(arrs.values)})
-            )
+            region_df = region_df.groupby(
+                ['sub', 'slide', 'section'], as_index=False
+            ).agg({'values': lambda arrs: np.concatenate(arrs.values)})
         else:
             raise ValueError('region_df has duplicate keys!')
     region_df[f'{measure}_{region}_values'] = df['values'].apply(summary_measure)