[easy] Fix line wrapping (#493)

Removes unnecessary line continuation markers.
spacetx · Aug 31, 2018 · 58db7c0 · 58db7c0
1 parent 342fbe1
commit 58db7c0
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Showing 5 changed files with 25 additions and 15 deletions.
diff --git a/starfish/codebook.py b/starfish/codebook.py
@@ -339,8 +339,10 @@ def to_json(self, filename: str) -> None:
             json.dump(code_array, f)
 
     @staticmethod
-    def _normalize_features(array: Union["Codebook", IntensityTable], norm_order) \
-            -> Tuple[Union["Codebook", IntensityTable], np.ndarray]:
+    def _normalize_features(
+            array: Union["Codebook", IntensityTable],
+            norm_order,
+    ) -> Tuple[Union["Codebook", IntensityTable], np.ndarray]:
         """unit normalize each feature of array
 
         Parameters

diff --git a/starfish/image/_filter/white_tophat.py b/starfish/image/_filter/white_tophat.py
@@ -48,8 +48,8 @@ def white_tophat(self, image: np.ndarray) -> np.ndarray:
         return white_tophat(image, selem=structuring_element)
 
     def run(
-            self, stack: ImageStack, in_place: bool=True, verbose: bool=False) \
-            -> Optional[ImageStack]:
+            self, stack: ImageStack, in_place: bool=True, verbose: bool=False
+    ) -> Optional[ImageStack]:
         """Perform filtering of an image stack
 
         Parameters

diff --git a/starfish/spots/_detector/combine_adjacent_features.py b/starfish/spots/_detector/combine_adjacent_features.py
@@ -115,8 +115,7 @@ def combine_adjacent_features(
 
     # now I need to make an IntensityTable from this thing.
     spots_df = pd.DataFrame(spots)
-    spots_df[Features.DISTANCE] = \
-        mean_pixel_traces[Features.DISTANCE]
+    spots_df[Features.DISTANCE] = mean_pixel_traces[Features.DISTANCE]
 
     # create new indexes for the output IntensityTable
     channel_index = mean_pixel_traces.indexes[Indices.CH]

diff --git a/starfish/spots/_detector/gaussian.py b/starfish/spots/_detector/gaussian.py
@@ -16,9 +16,15 @@
 class GaussianSpotDetector(SpotFinderAlgorithmBase):
 
     def __init__(
-            self, min_sigma: Number, max_sigma: Number, num_sigma: int, threshold: Number,
-            overlap=0.5, measurement_type='max', is_volume: bool=True, **kwargs) \
-            -> None:
+            self,
+            min_sigma: Number,
+            max_sigma: Number,
+            num_sigma: int,
+            threshold: Number,
+            overlap: float=0.5,
+            measurement_type='max',
+            is_volume: bool=True, **kwargs
+    ) -> None:
         """Multi-dimensional gaussian spot detector
 
         This method is a wrapper for skimage.feature.blob_log
@@ -107,10 +113,11 @@ def image_to_spots(self, data_image: Union[np.ndarray, xr.DataArray]) -> SpotAtt
         return SpotAttributes(rounded_blobs)
 
     def run(
-            self, data_stack: ImageStack,
+            self,
+            data_stack: ImageStack,
             blobs_image: Optional[Union[np.ndarray, xr.DataArray]]=None,
-            reference_image_from_max_projection: bool=False) \
-            -> IntensityTable:
+            reference_image_from_max_projection: bool=False,
+    ) -> IntensityTable:
         """find spots in an ImageStack
 
         Parameters

diff --git a/starfish/spots/_detector/local_max_peak_finder.py b/starfish/spots/_detector/local_max_peak_finder.py
@@ -124,10 +124,12 @@ def image_to_spots(self, image: np.ndarray) -> SpotAttributes:
         attributes['spot_id'] = np.arange(attributes.shape[0])
         return SpotAttributes(attributes)
 
-    def run(self, data_stack: ImageStack,
+    def run(
+            self,
+            data_stack: ImageStack,
             blobs_image: Optional[Union[np.ndarray, xr.DataArray]]=None,
-            reference_image_from_max_projection: bool=False) \
-            -> IntensityTable:
+            reference_image_from_max_projection: bool=False,
+    ) -> IntensityTable:
         """
         Find spots.