STYLE: Rename _unit_disk(r) to unit_disk(r)

broadinstitute · Jan 12, 2024 · 55a58b0 · 55a58b0
1 parent ba4e5fd
commit 55a58b0
Show file tree

Hide file tree

Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/ml4h/explorations.py b/ml4h/explorations.py
@@ -37,7 +37,7 @@
 from ml4h.plots import evaluate_predictions, subplot_rocs, subplot_scatters, plot_categorical_tmap_over_time
 from ml4h.defines import JOIN_CHAR, MRI_SEGMENTED_CHANNEL_MAP, CODING_VALUES_MISSING, CODING_VALUES_LESS_THAN_ONE
 from ml4h.defines import TENSOR_EXT, IMAGE_EXT, ECG_CHAR_2_IDX, ECG_IDX_2_CHAR, PARTNERS_CHAR_2_IDX, PARTNERS_IDX_2_CHAR, PARTNERS_READ_TEXT
-from ml4h.tensorize.tensor_writer_ukbb import _unit_disk
+from ml4h.tensorize.tensor_writer_ukbb import unit_disk
 
 from sklearn.pipeline import make_pipeline
 from sklearn.preprocessing import StandardScaler
@@ -815,7 +815,7 @@ def infer_stats_from_segmented_regions(args):
 
     # Structuring element used for the erosion
     if args.erosion_radius > 0:
-        structure = _unit_disk(args.erosion_radius)[np.newaxis, ..., np.newaxis]
+        structure = unit_disk(args.erosion_radius)[np.newaxis, ..., np.newaxis]
 
     # Setup for intensity thresholding
     do_intensity_thresh = args.intensity_thresh_in_structures and args.intensity_thresh_out_structure

diff --git a/ml4h/tensorize/tensor_writer_ukbb.py b/ml4h/tensorize/tensor_writer_ukbb.py
@@ -647,22 +647,22 @@ def _get_overlay_from_dicom(d, debug=False) -> Tuple[np.ndarray, np.ndarray]:
         short_side = min((max_pos[0] - min_pos[0]), (max_pos[1] - min_pos[1]))
         small_radius = max(MRI_MIN_RADIUS, short_side * MRI_SMALL_RADIUS_FACTOR)
         big_radius = max(MRI_MIN_RADIUS+1, short_side * MRI_BIG_RADIUS_FACTOR)
-        small_structure = _unit_disk(small_radius)
+        small_structure = unit_disk(small_radius)
         m1 = binary_closing(overlay, small_structure).astype(np.int)
-        big_structure = _unit_disk(big_radius)
+        big_structure = unit_disk(big_radius)
         m2 = binary_closing(overlay, big_structure).astype(np.int)
         anatomical_mask = m1 + m2
         ventricle_pixels = np.count_nonzero(anatomical_mask == MRI_SEGMENTED_CHANNEL_MAP['ventricle'])
         myocardium_pixels = np.count_nonzero(anatomical_mask == MRI_SEGMENTED_CHANNEL_MAP['myocardium'])
         if ventricle_pixels == 0 and myocardium_pixels > MRI_MAX_MYOCARDIUM:  # try to rescue small ventricles
-            erode_structure = _unit_disk(small_radius*1.5)
+            erode_structure = unit_disk(small_radius * 1.5)
             anatomical_mask = anatomical_mask - binary_erosion(m1, erode_structure).astype(np.int)
             ventricle_pixels = np.count_nonzero(anatomical_mask == MRI_SEGMENTED_CHANNEL_MAP['ventricle'])
             myocardium_pixels = np.count_nonzero(anatomical_mask == MRI_SEGMENTED_CHANNEL_MAP['myocardium'])
         return overlay, anatomical_mask, ventricle_pixels, myocardium_pixels
 
 
-def _unit_disk(r) -> np.ndarray:
+def unit_disk(r) -> np.ndarray:
     y, x = np.ogrid[-r: r + 1, -r: r + 1]
     return (x ** 2 + y ** 2 <= r ** 2).astype(np.int32)