linting

hippunfold/dags/proc_subgraph.py

@@ -19,7 +19,6 @@
 subgraphs = dict()
 
 for smk in glob("../workflow/rules/*.smk"):
-
     smk_name = re.findall(re.compile(r"/(\w+).smk"), smk)[0]
 
     with open(smk, "r") as f:

hippunfold/workflow/Snakefile

@@ -139,23 +139,11 @@ if config["modality"] == "hippb500":
 
 
 include: "rules/autotop.smk"
-
-
 include: "rules/warps.smk"
-
-
 include: "rules/gifti.smk"
-
-
 include: "rules/subfields.smk"
-
-
 include: "rules/resample_final_to_crop_native.smk"
-
-
 include: "rules/qc.smk"
-
-
 include: "rules/myelin_map.smk"
 
 

hippunfold/workflow/rules/common.smk

@@ -24,7 +24,6 @@ def get_modality_suffix(modality):
 
 
 def get_final_spec():
-
     if len(config["hemi"]) == 2:
         specs = expand(
             bids(
@@ -323,7 +322,6 @@ def get_final_subj_output():
 
 
 def get_final_output():
-
     if config["keep_work"]:
         subj_output = get_final_subj_output()
     else:

hippunfold/workflow/rules/download.smk

@@ -5,13 +5,9 @@ download_dir = get_download_dir()
 
 rule download_extract_atlas:
     params:
-        url=lambda wildcards: config["resource_urls"]["atlas"][
-            wildcards.atlas
-        ],
+        url=lambda wildcards: config["resource_urls"]["atlas"][wildcards.atlas],
     output:
-        unzip_dir=directory(
-            Path(download_dir) / "atlas" / "{atlas}"
-        ),
+        unzip_dir=directory(Path(download_dir) / "atlas" / "{atlas}"),
     container:
         config["singularity"]["autotop"]
     shadow:
@@ -23,13 +19,9 @@ rule download_extract_atlas:
 
 rule download_extract_template:
     params:
-        url=lambda wildcards: config["resource_urls"]["template"][
-            wildcards.template
-        ],
+        url=lambda wildcards: config["resource_urls"]["template"][wildcards.template],
     output:
-        unzip_dir=directory(
-            Path(download_dir) / "template" / "{template}"
-        ),
+        unzip_dir=directory(Path(download_dir) / "template" / "{template}"),
     container:
         config["singularity"]["autotop"]
     shadow:

hippunfold/workflow/rules/nnunet.smk

@@ -42,7 +42,6 @@ def get_nnunet_input(wildcards):
 
 
 def get_model_tar():
-
     if config["force_nnunet_model"]:
         model_name = config["force_nnunet_model"]
     else:
@@ -201,7 +200,6 @@ rule unflip_nnunet_nii:
 
 
 def get_f3d_ref(wildcards, input):
-
     if config["modality"] == "T2w":
         nii = Path(input.template_dir) / config["template_files"][config["template"]][
             "crop_ref"

hippunfold/workflow/rules/preproc_t1.smk

@@ -71,7 +71,6 @@ else:
 
 
 def reg_to_template_cmd(wildcards, input, output):
-
     ref = str(
         Path(input.template_dir)
         / config["template_files"][config["template"]][wildcards.modality].format(

hippunfold/workflow/rules/preproc_t2.smk

@@ -114,7 +114,6 @@ rule reg_t2_to_ref:
 
 
 def get_aligned_n4_t2(wildcards):
-
     # first get the number of floating t2s
     filtered = snakebids.filter_list(config["input_zip_lists"]["T2w"], wildcards)
     num_scans = len(filtered["subject"])
@@ -278,7 +277,6 @@ def get_inputs_compose_t2_xfm_corobl(wildcards):
         return {"t2_to_t1": t2_to_t1, "t1_to_cor": t1_to_cor}
 
     else:
-
         # xfm0: t2 to template
         t2_to_std = (
             bids(

hippunfold/workflow/rules/qc.smk

@@ -110,7 +110,6 @@ rule plot_subj_subfields:
 
 
 def get_bg_img_for_subfield_qc(wildcards):
-
     if config["modality"] == "hippb500":
         return bids(
             root=work,

hippunfold/workflow/rules/subfields.smk

@@ -123,7 +123,6 @@ rule label_subfields_from_vol_coords_corobl:
 
 
 def get_tissue_atlas_remapping(wildcards):
-
     mapping = config["tissue_atlas_mapping"]
 
     remap = []

hippunfold/workflow/scripts/constrain_surf_to_bbox.py

@@ -2,7 +2,6 @@
 import numpy as np
 
 with open(snakemake.log[0], "w") as sys.stdout:
-
     epsilon = 0.01
 
     # load gifti surf

hippunfold/workflow/scripts/create_warps.py

@@ -259,7 +259,9 @@ def summary(name, array):
 summary("displace_to_unfold_vec", displace_to_unfold_vec)
 
 # create new shape as 5d vector image in native space
-native_map_shape = np.ones(5,)
+native_map_shape = np.ones(
+    5,
+)
 native_map_shape[:3] = mask.shape
 native_map_shape[-1] = 3
 

hippunfold/workflow/scripts/gen_volume_tsv.py

@@ -15,7 +15,6 @@
 
 
 for in_img, hemi in zip(snakemake.input.segs, hemis):
-
     img_nib = nib.load(in_img)
     img = img_nib.get_fdata()
     zooms = img_nib.header.get_zooms()

hippunfold/workflow/scripts/laplace_coords.py

@@ -77,7 +77,6 @@
 
 # iterate until the solution doesn't change anymore (or reach max iters)
 for i in range(max_iters):
-
     # debug: save niftis to check progress
     #   if (i % 100 == 0):
     #       tonii = coords.copy()

hippunfold/workflow/scripts/laplace_coords_withinit.py

@@ -56,7 +56,6 @@
 
 # iterate until the solution doesn't change anymore (or reach max iters)
 for i in range(max_iters):
-
     # debug: save niftis to check progress
     #   if (i % 100 == 0):
     #       tonii = coords.copy()