isort: define & apply

Borda · Apr 1, 2021 · ed07413 · ed07413
1 parent 117973b
commit ed07413
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Showing 45 changed files with 201 additions and 168 deletions.
diff --git a/.github/workflows/code-format.yml b/.github/workflows/code-format.yml
@@ -38,19 +38,19 @@ jobs:
       - name: yapf
         run: yapf --diff --parallel --recursive .
 
-  #imports-check-isort:
-  #  runs-on: ubuntu-20.04
-  #  steps:
-  #    - uses: actions/checkout@master
-  #    - uses: actions/setup-python@v2
-  #      with:
-  #        python-version: 3.8
-  #    - name: Install isort
-  #      run: |
-  #        pip install isort
-  #        pip list
-  #    - name: isort
-  #      run: isort --check-only .
+  imports-check-isort:
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@master
+      - uses: actions/setup-python@v2
+        with:
+          python-version: 3.8
+      - name: Install isort
+        run: |
+          pip install isort
+          pip list
+      - name: isort
+        run: isort --check-only .
 
   #typing-check-mypy:
   #  runs-on: ubuntu-20.04

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -15,9 +15,9 @@
 import glob
 import inspect
 import os
+import re
 import shutil
 import sys
-import re
 
 import m2r
 

diff --git a/experiments_ovary_centres/gui_annot_center_correction.py b/experiments_ovary_centres/gui_annot_center_correction.py
@@ -43,8 +43,8 @@
 
 # http://matplotlib.org/users/navigation_toolbar.html
 import gtk
-from matplotlib.figure import Figure
 from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg
+from matplotlib.figure import Figure
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
 import imsegm.utilities.data_io as tl_data

diff --git a/experiments_ovary_centres/run_center_candidate_training.py b/experiments_ovary_centres/run_center_candidate_training.py
@@ -43,13 +43,13 @@
 import matplotlib.pyplot as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
-import imsegm.utilities.drawing as tl_visu
-import imsegm.superpixels as seg_spx
-import imsegm.descriptors as seg_fts
 import imsegm.classification as seg_clf
+import imsegm.descriptors as seg_fts
 import imsegm.labeling as seg_lbs
+import imsegm.superpixels as seg_spx
+import imsegm.utilities.data_io as tl_data
+import imsegm.utilities.drawing as tl_visu
+import imsegm.utilities.experiments as tl_expt
 
 # whether skip loading triplest CSV from previous run
 FORCE_RELOAD = False

diff --git a/experiments_ovary_centres/run_center_clustering.py b/experiments_ovary_centres/run_center_clustering.py
@@ -23,10 +23,12 @@
 import matplotlib.pylab as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import run_center_candidate_training as run_train
+
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import run_center_candidate_training as run_train
+import imsegm.utilities.experiments as tl_expt
+
 # import run_center_prediction as run_pred
 
 # Set experiment folders

diff --git a/experiments_ovary_centres/run_center_evaluation.py b/experiments_ovary_centres/run_center_evaluation.py
@@ -32,13 +32,14 @@
 import matplotlib.pyplot as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
-import imsegm.utilities.drawing as tl_visu
-import imsegm.annotation as seg_annot
 import run_center_candidate_training as run_train
-import run_center_prediction as run_detect
 import run_center_clustering as run_clust
+import run_center_prediction as run_detect
+
+import imsegm.annotation as seg_annot
+import imsegm.utilities.data_io as tl_data
+import imsegm.utilities.drawing as tl_visu
+import imsegm.utilities.experiments as tl_expt
 
 # whether skip loading triplest CSV from previous run
 FORCE_RELOAD = False

diff --git a/experiments_ovary_centres/run_center_prediction.py b/experiments_ovary_centres/run_center_prediction.py
@@ -23,12 +23,13 @@
 import pandas as pd
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.experiments as tl_expt
-import imsegm.utilities.data_io as tl_data
-import imsegm.classification as seg_clf
 import run_center_candidate_training as run_train
 import run_center_clustering as run_clust
 
+import imsegm.classification as seg_clf
+import imsegm.utilities.data_io as tl_data
+import imsegm.utilities.experiments as tl_expt
+
 FORCE_RERUN = False
 NAME_CSV_TRIPLES = run_train.NAME_CSV_TRIPLES
 NAME_CSV_TRIPLES_TEMP = os.path.splitext(NAME_CSV_TRIPLES)[0] + '__TEMP.csv'

diff --git a/experiments_ovary_centres/run_create_annotation.py b/experiments_ovary_centres/run_create_annotation.py
@@ -30,12 +30,13 @@
 import numpy as np
 import pandas as pd
 from scipy import ndimage
-from skimage import morphology, measure, draw
+from skimage import draw, measure, morphology
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import run_center_candidate_training as run_train
+
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.experiments as tl_expt
-import run_center_candidate_training as run_train
 
 NAME_DIR = 'annot_centres'
 PARAMS = run_train.CENTER_PARAMS

diff --git a/experiments_ovary_detect/run_RG2Sp_estim_shape-models.py b/experiments_ovary_detect/run_RG2Sp_estim_shape-models.py
@@ -21,8 +21,8 @@
 import pandas as pd
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.data_io as tl_data
 import imsegm.region_growing as tl_rg
+import imsegm.utilities.data_io as tl_data
 
 PATH_DATA = tl_data.update_path('data-images', absolute=True)
 PATH_IMAGES = os.path.join(tl_data.update_path('data-images'), 'drosophila_ovary_slice')

diff --git a/experiments_ovary_detect/run_egg_swap_orientation.py b/experiments_ovary_detect/run_egg_swap_orientation.py
@@ -19,9 +19,10 @@
 import numpy as np
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import run_ellipse_annot_match as r_match
+
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.experiments as tl_expt
-import run_ellipse_annot_match as r_match
 
 IMAGE_CHANNEL = 0  # image channel for mass extraction
 

diff --git a/experiments_ovary_detect/run_ellipse_annot_match.py b/experiments_ovary_detect/run_ellipse_annot_match.py
@@ -23,11 +23,11 @@
 import pandas as pd
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
-import imsegm.utilities.drawing as tl_visu
 # import segmentation.annotation as seg_annot
 import imsegm.ellipse_fitting as ell_fit
+import imsegm.utilities.data_io as tl_data
+import imsegm.utilities.drawing as tl_visu
+import imsegm.utilities.experiments as tl_expt
 
 NAME_CSV_RESULTS = 'info_ovary_images_ellipses.csv'
 OVERLAP_THRESHOLD = 0.

diff --git a/experiments_ovary_detect/run_ellipse_cut_scale.py b/experiments_ovary_detect/run_ellipse_cut_scale.py
@@ -22,10 +22,11 @@
 from skimage import transform
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import run_ellipse_annot_match as r_match
+
+import imsegm.ellipse_fitting as ell_fit
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.experiments as tl_expt
-import imsegm.ellipse_fitting as ell_fit
-import run_ellipse_annot_match as r_match
 
 COLUMNS_ELLIPSE = ['ellipse_xc', 'ellipse_yc', 'ellipse_a', 'ellipse_b', 'ellipse_theta']
 OVERLAP_THRESHOLD = 0.45

diff --git a/experiments_ovary_detect/run_export_user-annot-segm.py b/experiments_ovary_detect/run_export_user-annot-segm.py
@@ -27,15 +27,15 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
+import matplotlib.pylab as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pylab as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import imsegm.annotation as seg_annot
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import imsegm.annotation as seg_annot
+import imsegm.utilities.experiments as tl_expt
 
 NB_WORKERS = tl_expt.nb_workers(0.8)
 PATH_IMAGES = tl_data.update_path(os.path.join('data-images', 'drosophila_ovary_slice'))

diff --git a/experiments_ovary_detect/run_ovary_egg-segmentation.py b/experiments_ovary_detect/run_ovary_egg-segmentation.py
@@ -37,24 +37,25 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
 from scipy import ndimage
-from skimage import segmentation, morphology
-from skimage import measure, draw
+from skimage import draw, measure, morphology, segmentation
 # from sklearn.externals import joblib
 # from sklearn import metrics, cross_validation
 from skimage.measure.fit import EllipseModel
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+from morphsnakes import morphsnakes, multi_snakes
+
+import imsegm.ellipse_fitting as ell_fit
+import imsegm.region_growing as seg_rg
+import imsegm.superpixels as seg_spx
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import imsegm.superpixels as seg_spx
-import imsegm.region_growing as seg_rg
-import imsegm.ellipse_fitting as ell_fit
-from morphsnakes import morphsnakes, multi_snakes
+import imsegm.utilities.experiments as tl_expt
+
 # from libs import chanvese
 
 NB_WORKERS = tl_expt.nb_workers(0.8)

diff --git a/experiments_ovary_detect/run_ovary_segm_evaluation.py b/experiments_ovary_detect/run_ovary_segm_evaluation.py
@@ -26,16 +26,16 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 from sklearn import metrics
-import matplotlib.pyplot as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.experiments as tl_expt
+import imsegm.labeling as seg_lbs
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.drawing as tl_visu
-import imsegm.labeling as seg_lbs
+import imsegm.utilities.experiments as tl_expt
 
 EXPORT_VUSIALISATION = False
 NB_WORKERS = tl_expt.nb_workers(0.9)

diff --git a/experiments_segmentation/run_compute_stat_annot_segm.py b/experiments_segmentation/run_compute_stat_annot_segm.py
@@ -25,16 +25,16 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
-import pandas as pd
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
 from skimage.segmentation import relabel_sequential
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import imsegm.classification as seg_clf
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import imsegm.classification as seg_clf
+import imsegm.utilities.experiments as tl_expt
 
 NB_WORKERS = tl_expt.nb_workers(0.9)
 NAME_CVS_OVERALL = 'STATISTIC__%s___Overall.csv'

diff --git a/experiments_segmentation/run_eval_superpixels.py b/experiments_segmentation/run_eval_superpixels.py
@@ -26,18 +26,18 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+from run_segm_slic_model_graphcut import load_image, TYPES_LOAD_IMAGE
+
+import imsegm.labeling as seg_lbs
+import imsegm.superpixels as seg_spx
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import imsegm.superpixels as seg_spx
-import imsegm.labeling as seg_lbs
-from run_segm_slic_model_graphcut import load_image
-from run_segm_slic_model_graphcut import TYPES_LOAD_IMAGE
+import imsegm.utilities.experiments as tl_expt
 
 NB_WORKERS = tl_expt.nb_workers(0.9)
 PATH_IMAGES = os.path.join(tl_data.update_path('data-images'), 'drosophila_ovary_slice')

diff --git a/experiments_segmentation/run_segm_slic_classif_graphcut.py b/experiments_segmentation/run_segm_slic_classif_graphcut.py
@@ -42,29 +42,34 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
-from PIL import Image
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
+import skimage.color as sk_color
+from PIL import Image
 # from llvmpy._api.llvm.CmpInst import FCMP_OLE
 from skimage import segmentation
-import skimage.color as sk_color
 from sklearn import metrics
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
-import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
-import imsegm.utilities.drawing as tl_visu
-import imsegm.pipelines as seg_pipe
-import imsegm.labeling as seg_label
-import imsegm.descriptors as seg_fts
-import imsegm.classification as seg_clf
-import imsegm.superpixels as seg_spx
-import imsegm.graph_cuts as seg_gc
 from run_segm_slic_model_graphcut import (
-    arg_parse_params, load_image, parse_imgs_idx_path, get_idx_name, write_skip_file
+    arg_parse_params,
+    get_idx_name,
+    load_image,
+    parse_imgs_idx_path,
+    write_skip_file,
 )
 
+import imsegm.classification as seg_clf
+import imsegm.descriptors as seg_fts
+import imsegm.graph_cuts as seg_gc
+import imsegm.labeling as seg_label
+import imsegm.pipelines as seg_pipe
+import imsegm.superpixels as seg_spx
+import imsegm.utilities.data_io as tl_data
+import imsegm.utilities.drawing as tl_visu
+import imsegm.utilities.experiments as tl_expt
+
 NAME_EXPERIMENT = 'experiment_segm-Supervised'
 NB_WORKERS = tl_expt.nb_workers(0.9)
 

diff --git a/experiments_segmentation/run_segm_slic_model_graphcut.py b/experiments_segmentation/run_segm_slic_model_graphcut.py
@@ -37,21 +37,22 @@
     print('No display found. Using non-interactive Agg backend.')
     matplotlib.use('Agg')
 
-from PIL import Image
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
+from PIL import Image
 # from llvmpy._api.llvm.CmpInst import FCMP_OLE
 from skimage import segmentation
 from sklearn import metrics
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import imsegm.descriptors as seg_fts
+import imsegm.labeling as seg_lbs
+import imsegm.pipelines as seg_pipe
 import imsegm.utilities.data_io as tl_data
-import imsegm.utilities.experiments as tl_expt
 import imsegm.utilities.drawing as tl_visu
-import imsegm.pipelines as seg_pipe
-import imsegm.labeling as seg_lbs
-import imsegm.descriptors as seg_fts
+import imsegm.utilities.experiments as tl_expt
+
 # sometimes it freeze in "Cython: computing Colour means for image"
 seg_fts.USE_CYTHON = False
 

diff --git a/handling_annotations/run_image_color_quantization.py b/handling_annotations/run_image_color_quantization.py
@@ -25,9 +25,9 @@
 import numpy as np
 
 sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
+import imsegm.annotation as seg_annot
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.experiments as tl_expt
-import imsegm.annotation as seg_annot
 
 PATH_IMAGES = os.path.join('data-images', 'drosophila_ovary_slice', 'segm_rgb', '*.png')
 NB_WORKERS = tl_expt.nb_workers(0.9)