isort

m2g/functional/m2g_func.py

@@ -1,11 +1,13 @@
-import subprocess
-import yaml
 import os
-import regex as re
-from m2g.utils.gen_utils import run
-import sys
 import shutil
+import subprocess
+import sys
+
 import numpy as np
+import regex as re
+import yaml
+
+from m2g.utils.gen_utils import run
 
 
 def make_dataconfig(input_dir, sub, ses, anat, func, acquisition="alt+z", tr=2.0):

m2g/graph.py

@@ -9,28 +9,29 @@
 """
 
 
+import csv
 # standard library imports
 import os
 import time
-import csv
-from itertools import combinations
-from functools import reduce
 from collections import defaultdict
+from functools import reduce
+from itertools import combinations
 from pathlib import Path
 
-# package imports
-import numpy as np
+import matplotlib
 import networkx as nx
 import nibabel as nib
+# package imports
+import numpy as np
 from dipy.tracking._utils import _mapping_to_voxel, _to_voxel_coordinates
-from m2g.utils.gen_utils import timer
-import matplotlib
 from joblib import Parallel, delayed
 
+from m2g.utils.gen_utils import timer
+
 matplotlib.use("agg")
-from matplotlib import pyplot as plt
-from graspologic.utils import ptr
 from graspologic.plot import heatmap
+from graspologic.utils import ptr
+from matplotlib import pyplot as plt
 
 
 class GraphTools:

m2g/preproc.py

@@ -8,9 +8,10 @@
 TODO : depracate or change name. Add other preprocessing functions created from m2g_dwi_pipeline.
 """
 
+import subprocess
+
 # package imports
 import numpy as np
-import subprocess
 
 # m2g imports
 from m2g.utils import gen_utils

m2g/register.py

@@ -9,26 +9,24 @@
 
 # standard library imports
 import os
-from argparse import ArgumentParser
 import subprocess
+from argparse import ArgumentParser
 from pathlib import Path
 
 # package imports
 import nibabel as nib
 import numpy as np
-from nilearn.image import load_img
-from nilearn.image import math_img
-from dipy.tracking.streamline import deform_streamlines
 from dipy.io.streamline import load_trk
 from dipy.tracking import utils
+from dipy.tracking.streamline import deform_streamlines
+from nilearn.image import load_img, math_img
 
-# m2g imports
-from m2g.utils import gen_utils
-from m2g.utils import reg_utils
 from m2g.scripts import m2g_bids
-from m2g.stats.qa_skullstrip import gen_overlay_pngs
-from m2g.stats.qa_reg import reg_mri_pngs
 from m2g.stats.qa_fast import qa_fast_png
+from m2g.stats.qa_reg import reg_mri_pngs
+from m2g.stats.qa_skullstrip import gen_overlay_pngs
+# m2g imports
+from m2g.utils import gen_utils, reg_utils
 
 
 @gen_utils.timer

m2g/scripts/__init__.py

@@ -9,6 +9,4 @@
 m2g_cloud : for performing batch processing on AWS
 """
 
-from . import m2g_bids
-from . import m2g_cloud
-from . import m2g_dwi_pipeline
+from . import m2g_bids, m2g_cloud, m2g_dwi_pipeline

m2g/scripts/m2g_bids.py

@@ -12,25 +12,23 @@
 """
 
 
-# standard library imports
-import sys
-import shutil
 import glob
 import os
+import re
+import shutil
+# standard library imports
+import sys
 from argparse import ArgumentParser
+
 import numpy as np
 from numpy import genfromtxt
-import re
 
-# m2g imports
-from m2g.utils import cloud_utils
-from m2g.utils import gen_utils
-from m2g.utils.gen_utils import DirectorySweeper
-from m2g.utils.gen_utils import check_dependencies
-from m2g.utils.gen_utils import is_bids
-from m2g.utils.gen_utils import as_directory
+from m2g.functional.m2g_func import func_dir_reorg, m2g_func_worker
 from m2g.scripts.m2g_dwi_pipeline import m2g_dwi_worker
-from m2g.functional.m2g_func import m2g_func_worker, func_dir_reorg
+# m2g imports
+from m2g.utils import cloud_utils, gen_utils
+from m2g.utils.gen_utils import (DirectorySweeper, as_directory,
+                                 check_dependencies, is_bids)
 
 
 def get_atlas(atlas_dir, vox_size):

m2g/scripts/m2g_cloud.py

@@ -8,23 +8,22 @@
 For a tutorial on setting this up, see here : https://github.com/neurodata/m2g/blob/deploy/tutorials/Batch.ipynb
 """
 
+import json
+import os
+import re
 # standard library imports
 import subprocess
-import re
-import os
 import sys
-import json
-from copy import deepcopy
-from collections import OrderedDict
 from argparse import ArgumentParser
+from collections import OrderedDict
+from copy import deepcopy
 from pathlib import Path
 
 # m2g imports
 import m2g
 from m2g.utils import gen_utils
-from m2g.utils.cloud_utils import get_credentials
-from m2g.utils.cloud_utils import get_matching_s3_objects
-from m2g.utils.cloud_utils import s3_client
+from m2g.utils.cloud_utils import (get_credentials, get_matching_s3_objects,
+                                   s3_client)
 
 
 def batch_submit(

m2g/scripts/m2g_dwi_pipeline.py

@@ -8,33 +8,27 @@
 """
 
 
+# multithreading
+import multiprocessing as mp
+import os
 # standard library imports
 import shutil
 import time
+from argparse import ArgumentParser
 from datetime import datetime
-import os
 from pathlib import Path
-from argparse import ArgumentParser
+from subprocess import Popen
 
 # package imports
 import nibabel as nib
 import numpy as np
-from subprocess import Popen
-from dipy.tracking.streamline import Streamlines
 from dipy.io import read_bvals_bvecs
+from dipy.tracking.streamline import Streamlines
 
 # m2g imports
-from m2g import preproc
-from m2g import register
-from m2g import track
-from m2g import graph
-from m2g.utils import gen_utils
-from m2g.utils import reg_utils
-from m2g.utils import cloud_utils
+from m2g import graph, preproc, register, track
 from m2g.stats.qa_tractography import qa_tractography
-
-# multithreading
-import multiprocessing as mp
+from m2g.utils import cloud_utils, gen_utils, reg_utils
 
 # TODO : not sure why this is here, potentially remove
 os.environ["MPLCONFIGDIR"] = "/tmp/"

m2g/stats/qa_fast.py

@@ -1,8 +1,9 @@
 import matplotlib.pyplot as plt
-import numpy as np
 import nibabel as nb
-from scipy import ndimage
+import numpy as np
 from matplotlib.colors import LinearSegmentedColormap
+from scipy import ndimage
+
 from m2g.utils.qa_utils import pad_im
 
 

m2g/stats/qa_reg.py

@@ -13,18 +13,20 @@
 import os
 import re
 import sys
-import numpy as np
+from argparse import ArgumentParser
+
+import matplotlib as mpl
 import nibabel as nb
+import numpy as np
+from matplotlib.colors import LinearSegmentedColormap
+from scipy import ndimage
+
 from m2g.utils.gen_utils import get_braindata, get_filename
 from m2g.utils.qa_utils import get_min_max, opaque_colorscale, pad_im
-from argparse import ArgumentParser
-from scipy import ndimage
-from matplotlib.colors import LinearSegmentedColormap
-import matplotlib as mpl
 
 mpl.use("Agg")  # very important above pyplot import
-from nilearn.plotting.edge_detect import _edge_map as edge_map
 import matplotlib.pyplot as plt
+from nilearn.plotting.edge_detect import _edge_map as edge_map
 
 
 def reg_mri_pngs(

m2g/stats/qa_skullstrip.py

@@ -16,18 +16,20 @@
 import os
 import re
 import sys
-import numpy as np
-import nibabel as nb
 from argparse import ArgumentParser
-from scipy import ndimage
-from matplotlib.colors import LinearSegmentedColormap
+
 import matplotlib as mpl
+import nibabel as nb
+import numpy as np
+from matplotlib.colors import LinearSegmentedColormap
+from scipy import ndimage
 
 mpl.use("Agg")  # very important above pyplot import
-from nilearn.plotting.edge_detect import _edge_map as edge_map
 import matplotlib.pyplot as plt
+from nilearn.plotting.edge_detect import _edge_map as edge_map
+
+from m2g.utils.gen_utils import get_braindata, get_filename
 from m2g.utils.qa_utils import get_min_max, opaque_colorscale, pad_im
-from m2g.utils.gen_utils import get_filename, get_braindata
 
 
 def gen_overlay_pngs(

m2g/stats/qa_tensor.py

@@ -12,15 +12,16 @@
 import warnings
 
 warnings.simplefilter("ignore")
-from argparse import ArgumentParser
-from scipy import ndimage
-import numpy as np
-import nibabel as nb
-import matplotlib
 import itertools
+from argparse import ArgumentParser
 
-from dipy.viz import window, actor
+import matplotlib
+import nibabel as nb
+import numpy as np
+from dipy.viz import actor, window
 from fury.actor import orient2rgb
+from scipy import ndimage
+
 from m2g.utils import qa_utils
 
 matplotlib.use("Agg")  # very important above pyplot import

m2g/stats/qa_tractography.py

@@ -1,12 +1,12 @@
-import nibabel as nib
-import numpy as np
-import matplotlib.pyplot as plt
 import os
 
-from fury import actor, window, colormap, ui
+import matplotlib.pyplot as plt
+import nibabel as nib
+import numpy as np
 from dipy.tracking.streamline import Streamlines
-from PIL import Image
+from fury import actor, colormap, ui, window
 from matplotlib.colors import LinearSegmentedColormap
+from PIL import Image
 
 
 def combine_plot(qa_out_path, brain_path):

m2g/track.py

@@ -11,28 +11,26 @@
 # system imports
 import os
 
+import nibabel as nib
 # external package imports
 import numpy as np
-import nibabel as nib
-
+from dipy.data import get_sphere
+from dipy.direction import ProbabilisticDirectionGetter, peaks_from_model
+from dipy.reconst.csdeconv import (ConstrainedSphericalDeconvModel,
+                                   recursive_response)
+from dipy.reconst.dti import TensorModel, fractional_anisotropy, quantize_evecs
+from dipy.reconst.shm import CsaOdfModel
+from dipy.tracking import utils
+from dipy.tracking.local_tracking import (LocalTracking,
+                                          ParticleFilteringTracking)
+from dipy.tracking.stopping_criterion import (ActStoppingCriterion,
+                                              BinaryStoppingCriterion,
+                                              CmcStoppingCriterion)
 # dipy imports
 from dipy.tracking.streamline import Streamlines
-from dipy.tracking import utils
-from dipy.tracking.local_tracking import LocalTracking
-from dipy.tracking.local_tracking import ParticleFilteringTracking
-from dipy.tracking.stopping_criterion import BinaryStoppingCriterion
-from dipy.tracking.stopping_criterion import ActStoppingCriterion
-from dipy.tracking.stopping_criterion import CmcStoppingCriterion
-
-from dipy.reconst.dti import fractional_anisotropy, TensorModel, quantize_evecs
-from dipy.reconst.shm import CsaOdfModel
-from dipy.reconst.csdeconv import ConstrainedSphericalDeconvModel, recursive_response
-
-from dipy.data import get_sphere
-from dipy.direction import peaks_from_model, ProbabilisticDirectionGetter
-from m2g.utils.gen_utils import timer
 
 from m2g.stats import qa_tensor
+from m2g.utils.gen_utils import timer
 
 
 def build_seed_list(mask_img_file, stream_affine, dens):

m2g/utils/cloud_utils.py

@@ -5,10 +5,10 @@
 Contains utility functions for working on the cloud with AWS.
 """
 
-# standard library imports
-from configparser import ConfigParser
 import os
 import sys
+# standard library imports
+from configparser import ConfigParser
 
 # package imports
 import boto3