removed superflous print statements

PyNutil/coordinate_extraction.py

@@ -138,14 +138,7 @@ def folder_to_atlas_space(
     points_len = [len(points) for points in points_list]
     centroids_len = [len(centroids) for centroids in centroids_list]
     points = np.concatenate(points_list)
-    print("points shape: ",points.shape)
     centroids = np.concatenate(centroids_list)
-    print("centroids shape: ",centroids.shape)
-    print("Number of points: ", len(points))
-    print("Number of centroids: ", len(centroids))
-    print("points_len: ", points_len)
-    print("points: ", points)
-    print("points first: ", points[0])
 
     return (
         np.array(points),
@@ -195,7 +188,6 @@ def segmentation_to_atlas_space(
         )
     if method in ["per_pixel", "all"]:
         scaled_y, scaled_x = get_scaled_pixels(segmentation, pixel_id, y_scale, x_scale)
-    print(f"{segmentation_path} \nNumber of objects: {len(scaled_centroidsY)}\nNumber of pixels: {len(scaled_y)}")
 
     if non_linear:
         if "markers" in slice:
@@ -229,7 +221,9 @@ def segmentation_to_atlas_space(
         centroids = transform_to_atlas_space(
             slice["anchoring"], centroids_new_y, centroids_new_x, reg_height, reg_width
         )
-    print(f"Finished and points len is: {len(points)} and centroids len is: {len(centroids)}")
+    print(
+        f"Finished and points len is: {len(points)} and centroids len is: {len(centroids)}"
+    )
     points_list[index] = np.array(points)
     centroids_list[index] = np.array(centroids)
 

PyNutil/counting_and_load.py

@@ -17,23 +17,23 @@ def label_points(points, label_volume, scale_factor=1):
     x = points[:, 0]
     y = points[:, 1]
     z = points[:, 2]
-    print(x[0], y[0], z[0])
 
     # make sure the points are within the volume
     x[x < 0] = 0
     y[y < 0] = 0
     z[z < 0] = 0
-    mask = (x > label_volume.shape[0] - 1) | (y > label_volume.shape[1] - 1) | (z > label_volume.shape[2] - 1)
+    mask = (
+        (x > label_volume.shape[0] - 1)
+        | (y > label_volume.shape[1] - 1)
+        | (z > label_volume.shape[2] - 1)
+    )
     x[mask] = 0
     y[mask] = 0
     z[mask] = 0
-    print('total mask: ')
-    print(np.sum(mask))
+
     # Get the label value for each point
-    print(x[0], y[0], z[0])
     labels = label_volume[x, y, z]
-    print('label sum: ')
-    print(np.sum(labels))
+
     return labels
 
 

PyNutil/generate_target_slice.py

@@ -7,7 +7,6 @@ def generate_target_slice(alignment, volume):
     bounds = [455, 527, 319]
     X_size = np.sqrt(np.sum(np.square((Ux, Uy, Uz))))
     Z_size = np.sqrt(np.sum(np.square((Vx, Vy, Vz))))
-    print(X_size, Z_size)
     X_size = np.round(X_size).astype(int)
     Z_size = np.round(Z_size).astype(int)
     # make this into a grid (0,0) to (320,456)

PyNutil/main.py

@@ -272,7 +272,6 @@ class PyNutil:
             self.segmentation_filenames,
             self.per_section_df,
         ):
-            
             split_fn = fn.split("/")[-1].split(".")[0]
             df.to_csv(
                 f"{output_folder}/per_section_reports/{split_fn}.csv",