style: standardize import order using isort

HD_BET/config.py

@@ -1,8 +1,10 @@
+from abc import abstractmethod
+
 import numpy as np
 import torch
-from HD_BET.utils import SetNetworkToVal, softmax_helper
-from abc import abstractmethod
+
 from HD_BET.network_architecture import Network
+from HD_BET.utils import SetNetworkToVal, softmax_helper
 
 
 class BaseConfig(object):

HD_BET/data_loading.py

@@ -1,5 +1,5 @@
-import SimpleITK as sitk
 import numpy as np
+import SimpleITK as sitk
 from skimage.transform import resize
 
 

HD_BET/hd_bet_cli.py

@@ -1,9 +1,10 @@
 #!/usr/bin/env python
 
 import os
+
+import HD_BET
 from HD_BET.run import run_hd_bet
 from HD_BET.utils import maybe_mkdir_p, subfiles
-import HD_BET
 
 
 def main():

HD_BET/network_architecture.py

@@ -1,6 +1,7 @@
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+
 from HD_BET.utils import softmax_helper
 
 

HD_BET/predict_case.py

@@ -1,5 +1,5 @@
-import torch
 import numpy as np
+import torch
 
 
 def pad_patient_3D(patient, shape_must_be_divisible_by=16, min_size=None):

HD_BET/run.py

@@ -1,12 +1,15 @@
-import torch
+import imp
+import os
+
 import numpy as np
 import SimpleITK as sitk
+import torch
+
+import HD_BET
 from HD_BET.data_loading import load_and_preprocess, save_segmentation_nifti
 from HD_BET.predict_case import predict_case_3D_net
-import imp
-from HD_BET.utils import postprocess_prediction, SetNetworkToVal, get_params_fname, maybe_download_parameters
-import os
-import HD_BET
+from HD_BET.utils import (SetNetworkToVal, get_params_fname,
+                          maybe_download_parameters, postprocess_prediction)
 
 
 def apply_bet(img, bet, out_fname):

HD_BET/utils.py

@@ -1,9 +1,11 @@
+import os
 from urllib.request import urlopen
-import torch
-from torch import nn
+
 import numpy as np
+import torch
 from skimage.morphology import label
-import os
+from torch import nn
+
 from HD_BET.paths import folder_with_parameter_files