label hist. & PEP8 (#16)

* fix label histogram
* pep8 @imSegm
* pep8 @Experiments
* remove default dicts
* add doctests
* use flake8 & unset DISPLAY
* refactor CircleCI
* reinstall Morph-snakes
* add CodeFactor

.codecov.yml

@@ -20,7 +20,7 @@ coverage:
     # https://github.com/codecov/support/wiki/Patch-Status
     patch:
       default:
-        against: parent
+        against: auto
         target: 30% # specify the target "X%" coverage to hit
         threshold: 50% # allow this much decrease on patch
     changes: false

.shippable.yml

@@ -16,6 +16,7 @@ env:
   global:
     - CI_REPORTS=shippable/testresults
     - COVERAGE_REPORTS=shippable/codecoverage
+    - DISPLAY=""
 
 language: python
 
@@ -39,7 +40,7 @@ install:
   - mkdir libs
 
   - pip install -r requirements.txt
-  - pip install "nose>=1.3.7" coverage codecov "pytest>=3.0.5"
+  - pip install "nose>=1.3.7" coverage codecov "pytest>=3.0.5" flake8
 
 script:
   - mkdir mkdir output && mkdir results
@@ -49,6 +50,7 @@ script:
   # - nosetests -v --with-xunit --xunit-file=$CI_REPORTS/nosetests.xml
   - nosetests -v --exe --with-doctest --with-xunit --with-coverage --cover-package=imsegm --xunit-file=$CI_REPORTS/nosetests.xml
   - python setup.py check -m -s
+  - flake8 . --ignore=E402,E731 --max-line-length=100
 
   # ANNOTATION section
   - python handling_annotations/run_image_color_quantization.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png"
@@ -72,10 +74,7 @@ script:
   - python experiments_ovary_centres/run_center_evaluation.py
 
   # download MorphSnake
-  - cd $root/libs && git clone https://github.com/Borda/morph-snakes.git
-  - cd $root/libs/morph-snakes && pip install -r requirements.txt
-  - cd $root/libs/morph-snakes && python setup.py install
-  - cd $root
+  - pip install git+https://github.com/Borda/morph-snakes.git
   # REGION GROWING section
   - rm -r -f results && mkdir results
   - python experiments_ovary_detect/run_RG2Sp_estim_shape-models.py

.travis.yml

@@ -8,6 +8,7 @@
 env:
   global:
     - CODACY_PROJECT_TOKEN=ea6533a96dfb4b6a9b6b45fc134fabdf
+    - DISPLAY=""
 
 language: python
 
@@ -30,7 +31,7 @@ install:
   - mkdir libs
 
   - pip install -r requirements.txt
-  - pip install nose coverage codecov pytest codacy-coverage check-manifest
+  - pip install nose coverage codecov pytest codacy-coverage check-manifest flake8
 
 before_script:
   - mkdir output && mkdir results
@@ -42,6 +43,7 @@ script:
   - python setup.py build_ext --inplace
   # - pytest imsegm -v --doctest-modules
   - nosetests imsegm -v --exe --with-doctest --with-xunit --with-coverage --cover-package=imsegm
+  - flake8 . --ignore=E402,E731 --max-line-length=100
   - python setup.py install
 
 after_success:

README.md

@@ -6,6 +6,7 @@
 [![Run Status](https://api.shippable.com/projects/5962ea48a125960700c197f8/badge?branch=master)](https://app.shippable.com/github/Borda/pyImSegm)
 [![Coverage Badge](https://api.shippable.com/projects/5962ea48a125960700c197f8/coverageBadge?branch=master)](https://app.shippable.com/github/Borda/pyImSegm)
 [![CircleCI](https://circleci.com/gh/Borda/pyImSegm.svg?style=svg&circle-token=a30180a28ae7e490c0c0829d1549fcec9a5c59d0)](https://circleci.com/gh/Borda/pyImSegm)
+[![CodeFactor](https://www.codefactor.io/repository/github/borda/pyimsegm/badge)](https://www.codefactor.io/repository/github/borda/pyimsegm)
 
 
 ## Superpixel segmentation with GraphCut regularisation
@@ -281,11 +282,7 @@ In case you do not have estimated object centers, you can use [plugins](ij_macro
 
 **Note:** install multi-snake package which is used in multi-method segmentation experiment.
 ```bash
-cd libs 
-git clone https://github.com/Borda/morph-snakes.git
-cd morph-snakes 
-pip install -r requirements.txt
-python setup.py install
+pip install --user git+https://github.com/Borda/morph-snakes.git
 ```
 
 **Experiment sequence is following:**

circle.yml

@@ -13,7 +13,8 @@ jobs:
               sudo apt-get update
               sudo apt-get install tk-dev pkg-config python-dev python-tk
               sudo pip install --upgrade pip setuptools
-              sudo pip install nose coverage pytest pytest-cov
+              sudo pip install nose coverage pytest pytest-cov flake8
+              sudo pip install -U backports.functools_lru_cache  # required for matplotlib @py2
               pip install -r requirements.txt --user
 
         # BUILDING
@@ -26,44 +27,56 @@ jobs:
 
         # TESTING
         - run:
-            name: Testing
+            name: Testing and Formating
             command: |
+              unset DISPLAY
               coverage run --source imsegm -m py.test imsegm -v --doctest-modules --junitxml=test-reports/pytest_junit.xml
               python setup.py check -m -s
+              flake8 . --ignore=E402,E731 --max-line-length=100
 
         # ANNOTATION section
-        - run: python handling_annotations/run_image_color_quantization.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png"
-        - run: python handling_annotations/run_image_color_quantization.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png" -m position
-        - run: python handling_annotations/run_image_convert_label_color.py -imgs "./data_images/drosophila_ovary_slice/segm/*.png" -out ./data_images/drosophila_ovary_slice/segm_rgb
-        - run: python handling_annotations/run_image_convert_label_color.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png" -out ./data_images/drosophila_ovary_slice/segm
-        - run: python handling_annotations/run_overlap_images_segms.py  -imgs "./data_images/drosophila_ovary_slice/image/*.jpg" -segs ./data_images/drosophila_ovary_slice/segm -out ./results/overlap_ovary_segment
-        - run: python handling_annotations/run_segm_annot_inpaint.py -imgs "./data_images/drosophila_ovary_slice/segm/*.png" --label 0
-        - run: python handling_annotations/run_segm_annot_relabel.py -imgs "./data_images/drosophila_ovary_slice/center_levels/*.png" -out ./results/relabel_center_levels
+        - run:
+            name: Annotations
+            command: |
+              python handling_annotations/run_image_color_quantization.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png"
+              python handling_annotations/run_image_color_quantization.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png" -m position
+              python handling_annotations/run_image_convert_label_color.py -imgs "./data_images/drosophila_ovary_slice/segm/*.png" -out ./data_images/drosophila_ovary_slice/segm_rgb
+              python handling_annotations/run_image_convert_label_color.py -imgs "./data_images/drosophila_ovary_slice/segm_rgb/*.png" -out ./data_images/drosophila_ovary_slice/segm
+              python handling_annotations/run_overlap_images_segms.py  -imgs "./data_images/drosophila_ovary_slice/image/*.jpg" -segs ./data_images/drosophila_ovary_slice/segm -out ./results/overlap_ovary_segment
+              python handling_annotations/run_segm_annot_inpaint.py -imgs "./data_images/drosophila_ovary_slice/segm/*.png" --label 0
+              python handling_annotations/run_segm_annot_relabel.py -imgs "./data_images/drosophila_ovary_slice/center_levels/*.png" -out ./results/relabel_center_levels
 
         # SEGMENTATION section
-        - run: python experiments_segmentation/run_compute_stat_annot_segm.py -a "data_images/drosophila_ovary_slice/annot_struct/*.png" -s "data_images/drosophila_ovary_slice/segm/*.png" --visual
-        - run: python experiments_segmentation/run_segm_slic_model_graphcut.py -i "data_images/drosophila_disc/image/img_[5,6].jpg" -cfg ./experiments_segmentation/sample_config.json --visual
-        - run: python experiments_segmentation/run_segm_slic_classif_graphcut.py -l data_images/drosophila_ovary_slice/list_imgs-annot-struct_short.csv -i "data_images/drosophila_ovary_slice/image/insitu41*.jpg" -cfg ./experiments_segmentation/sample_config.json --visual
+        - run:
+            name: Segmentation
+            command: |
+              python experiments_segmentation/run_compute_stat_annot_segm.py -a "data_images/drosophila_ovary_slice/annot_struct/*.png" -s "data_images/drosophila_ovary_slice/segm/*.png" --visual
+              python experiments_segmentation/run_segm_slic_model_graphcut.py -i "data_images/drosophila_disc/image/img_[5,6].jpg" -cfg ./experiments_segmentation/sample_config.json --visual
+              python experiments_segmentation/run_segm_slic_classif_graphcut.py -l data_images/drosophila_ovary_slice/list_imgs-annot-struct_short.csv -i "data_images/drosophila_ovary_slice/image/insitu41*.jpg" -cfg ./experiments_segmentation/sample_config.json --visual
 
         # CENTER DETECT. section
-        - run: python experiments_ovary_centres/run_create_annotation.py
-        - run: python experiments_ovary_centres/run_center_candidate_training.py
-        - run: python experiments_ovary_centres/run_center_prediction.py
-        - run: python experiments_ovary_centres/run_center_clustering.py
-        - run: python experiments_ovary_centres/run_center_evaluation.py
+        - run:
+            name: Center detection
+            command: |
+              python experiments_ovary_centres/run_create_annotation.py
+              python experiments_ovary_centres/run_center_candidate_training.py
+              python experiments_ovary_centres/run_center_prediction.py
+              python experiments_ovary_centres/run_center_clustering.py
+              python experiments_ovary_centres/run_center_evaluation.py
 
-        # download MorphSnake
-        - run: cd libs && git clone https://github.com/Borda/morph-snakes.git
-        - run: cd libs/morph-snakes && pip install --user -r requirements.txt && python setup.py install --user
         # REGION GROWING section
-        - run: python experiments_ovary_detect/run_RG2Sp_estim_shape-models.py
-        - run: python experiments_ovary_detect/run_ovary_egg-segmentation.py -m ellipse_moments ellipse_ransac_mmt ellipse_ransac_crit GC_pixels-large GC_pixels-shape GC_slic-small GC_slic-shape rg2sp_greedy-single rg2sp_GC-mixture watershed_morph
-        - run: python experiments_ovary_detect/run_ovary_segm_evaluation.py --visual
-        - run: python experiments_ovary_detect/run_export_user-annot-segm.py
-        - run: python experiments_ovary_detect/run_cut_segmented_objects.py
-        - run: python experiments_ovary_detect/run_ellipse_annot_match.py
-        - run: python experiments_ovary_detect/run_ellipse_cut_scale.py
-        - run: python experiments_ovary_detect/run_egg_swap_orientation.py
+        - run:
+            name: Region Growing
+            command: |
+              pip install --user git+https://github.com/Borda/morph-snakes.git
+              python experiments_ovary_detect/run_RG2Sp_estim_shape-models.py
+              python experiments_ovary_detect/run_ovary_egg-segmentation.py -m ellipse_moments ellipse_ransac_mmt ellipse_ransac_crit GC_pixels-large GC_pixels-shape GC_slic-small GC_slic-shape rg2sp_greedy-single rg2sp_GC-mixture watershed_morph
+              python experiments_ovary_detect/run_ovary_segm_evaluation.py --visual
+              python experiments_ovary_detect/run_export_user-annot-segm.py
+              python experiments_ovary_detect/run_cut_segmented_objects.py
+              python experiments_ovary_detect/run_ellipse_annot_match.py
+              python experiments_ovary_detect/run_ellipse_cut_scale.py
+              python experiments_ovary_detect/run_egg_swap_orientation.py
 
         # PASSING
         - run:

experiments_ovary_centres/gui_annot_center_correction.py

@@ -44,7 +44,7 @@
 from matplotlib.figure import Figure
 from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg
 
-sys.path += [os.path.abspath('.'), os.path.abspath('..')] # Add path to root
+sys.path += [os.path.abspath('.'), os.path.abspath('..')]  # Add path to root
 import imsegm.utilities.data_io as tl_data
 import imsegm.utilities.drawing as tl_visu
 
@@ -87,7 +87,8 @@ def arg_parse_params():
                         help='path to file with complete info', default=None)
     params = vars(parser.parse_args())
     for k in (k for k in params if 'path' in k):
-        if params[k] is None: continue
+        if params[k] is None:
+            continue
         params[k] = os.path.abspath(os.path.expanduser(params[k]))
         p = os.path.dirname(params[k]) if '*' in params[k] else params[k]
         assert os.path.exists(p), 'missing: %s' % p
@@ -145,8 +146,8 @@ def set_false_negative(df_points, mask_eggs):
         if sum(labels) == 0:
             pos = ndimage.measurements.center_of_mass(mask)
             df_points = df_points.append(
-                            {'X': pos[1], 'Y': pos[0], 'label': 1, 'change': 1},
-                            ignore_index=True)
+                {'X': pos[1], 'Y': pos[0], 'label': 1, 'change': 1},
+                ignore_index=True)
     return df_points
 
 
@@ -266,7 +267,7 @@ def add_point_correction(x, y, changing=1, limit_dist=DICT_LIMIT_CORRECT):
     else:
         # add new point
         df_center_labeled = df_center_labeled.append(
-            {'X': x, 'Y': y,  'label': 1, 'change': 1}, ignore_index=True)
+            {'X': x, 'Y': y, 'label': 1, 'change': 1}, ignore_index=True)
 
     canvas_update_image_centers()
 
@@ -354,7 +355,7 @@ def main(params):
     actual_idx = 0
     paths_img_csv = load_paths_image_csv(params)
     logging.info('loaded %i pairs (image & centers)', len(paths_img_csv))
-    assert len(paths_img_csv) > 0, 'missing paths image - csv'
+    assert paths_img_csv, 'missing paths image - csv'
 
     if params['path_info'] is not None and os.path.isfile(params['path_info']):
         df_info_all = pd.read_csv(params['path_info'], sep='\t', index_col=0)