Formatting (#113)

* formatting and autoformat * autoformat workflow * Format code with black * Format code with black --------- Co-authored-by: louisblankemeier <[email protected]>
StanfordMIMI · Sep 25, 2023 · 0d063ee · 0d063ee
1 parent 5f4e282
commit 0d063ee
Show file tree

Hide file tree

Showing 7 changed files with 47 additions and 15 deletions.
diff --git a/.github/workflows/format.yml b/.github/workflows/format.yml
@@ -0,0 +1,33 @@
+name: Format code
+
+on:
+    push:
+      branches: [ 'master' ]
+    pull_request:
+      branches: [ 'master' ]
+
+jobs:
+  format:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Format code with black
+        run: |
+          pip install black
+          black .
+      - name: Sort imports with isort
+        run: |
+          pip install isort
+          isort .
+      - name: Remove unused imports with autoflake
+        run: |
+          pip install autoflake
+          autoflake --in-place --remove-all-unused-imports --remove-unused-variables --recursive .
+      - name: Commit changes
+        uses: EndBug/add-and-commit@v4
+        with:
+          author_name: ${{ github.actor }}
+          author_email: ${{ github.actor }}@users.noreply.github.com
+          message: "Format code with black"
+          add: "."
+          branch: ${{ github.ref }}
diff --git a/.gitignore b/.gitignore
@@ -44,6 +44,7 @@ docs/_build
 # ignore yml file
 *.yml
 *.yaml
+!.github/workflows/format.yml
 
 # ignore images
 *.png

diff --git a/comp2comp/aaa/aaa.py b/comp2comp/aaa/aaa.py
@@ -15,9 +15,7 @@
 import pandas as pd
 import pydicom
 import wget
-from totalsegmentator.libs import (
-    nostdout,
-)
+from totalsegmentator.libs import nostdout
 
 from comp2comp.inference_class_base import InferenceClass
 
@@ -142,7 +140,6 @@ def spine_seg(
         from totalsegmentator.nnunet import nnUNet_predict_image
 
         with nostdout():
-
             img, seg = nnUNet_predict_image(
                 input_path,
                 output_path,
@@ -189,7 +186,6 @@ def normalize_img(self, img: np.ndarray) -> np.ndarray:
         return (img - img.min()) / (img.max() - img.min())
 
     def __call__(self, inference_pipeline):
-
         axial_masks = (
             inference_pipeline.axial_masks
         )  # list of 2D numpy arrays of shape (512, 512)
@@ -223,7 +219,6 @@ def __call__(self, inference_pipeline):
         diameterDict = {}
 
         for i in range(len(ct_img)):
-
             mask = axial_masks[i].astype("uint8")
 
             img = ct_img[i]
@@ -236,10 +231,11 @@ def __call__(self, inference_pipeline):
             contours, _ = cv2.findContours(mask, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
 
             if len(contours) != 0:
-
                 areas = [cv2.contourArea(c) for c in contours]
                 sorted_areas = np.sort(areas)
 
+                areas = [cv2.contourArea(c) for c in contours]
+                sorted_areas = np.sort(areas)
                 contours = contours[areas.index(sorted_areas[-1])]
 
                 img.copy()

diff --git a/comp2comp/aortic_calcium/aortic_calcium_visualization.py b/comp2comp/aortic_calcium/aortic_calcium_visualization.py
@@ -10,7 +10,6 @@ def __init__(self):
         super().__init__()
 
     def __call__(self, inference_pipeline):
-
         self.output_dir = inference_pipeline.output_dir
         self.output_dir_images_organs = os.path.join(self.output_dir, "images/")
         inference_pipeline.output_dir_images_organs = self.output_dir_images_organs
@@ -26,7 +25,6 @@ def __init__(self):
         super().__init__()
 
     def __call__(self, inference_pipeline):
-
         metrics = inference_pipeline.metrics
 
         inference_pipeline.csv_output_dir = os.path.join(

diff --git a/comp2comp/contrast_phase/contrast_phase.py b/comp2comp/contrast_phase/contrast_phase.py
@@ -72,7 +72,6 @@ def run_segmentation(
         from totalsegmentator.nnunet import nnUNet_predict_image
 
         with nostdout():
-
             img, seg = nnUNet_predict_image(
                 input_path,
                 output_path,

diff --git a/comp2comp/hip/hip_utils.py b/comp2comp/hip/hip_utils.py
@@ -41,7 +41,11 @@ def compute_rois(medical_volume, segmentation, model, output_dir, save=False):
     ) = get_femural_head_roi(
         right_femur_mask, medical_volume, output_dir, "right_intertrochanter"
     )
-    (left_neck_roi, left_neck_centroid, left_neck_hu,) = get_femural_neck_roi(
+    (
+        left_neck_roi,
+        left_neck_centroid,
+        left_neck_hu,
+    ) = get_femural_neck_roi(
         left_femur_mask,
         medical_volume,
         left_intertrochanter_roi,
@@ -50,7 +54,11 @@ def compute_rois(medical_volume, segmentation, model, output_dir, save=False):
         left_head_centroid,
         output_dir,
     )
-    (right_neck_roi, right_neck_centroid, right_neck_hu,) = get_femural_neck_roi(
+    (
+        right_neck_roi,
+        right_neck_centroid,
+        right_neck_hu,
+    ) = get_femural_neck_roi(
         right_femur_mask,
         medical_volume,
         right_intertrochanter_roi,

diff --git a/comp2comp/spine/spine.py b/comp2comp/spine/spine.py
@@ -137,7 +137,6 @@ def spine_seg(
         from totalsegmentator.nnunet import nnUNet_predict_image
 
         with nostdout():
-
             img, seg = nnUNet_predict_image(
                 input_path,
                 output_path,
@@ -295,7 +294,6 @@ def __init__(self):
         super().__init__()
 
     def __call__(self, inference_pipeline):
-
         dicom_files, names, inferior_superior_centers = spine_utils.find_spine_dicoms(
             inference_pipeline.centroids_3d,
             inference_pipeline.dicom_series_path,
@@ -321,7 +319,6 @@ def __init__(self, format="png"):
         self.format = format
 
     def __call__(self, inference_pipeline):
-
         output_path = inference_pipeline.output_dir
         spine_model_type = inference_pipeline.spine_model_type