Cleanup trailing whitespace

README.md

@@ -116,7 +116,7 @@ Running the following command to generate the configuration file
 palom-svs-helper -i "Y:\DATA\SARDANA\MIHC\768473\RAW" -n "*Hem*" -o "Y:\DATA\SARDANA\MIHC\768473\RAW\palom\768473.ome.tif" -c "Y:\DATA\SARDANA\MIHC\768473\768473.yml"
 ```
 
-And the resulting `Y:\DATA\SARDANA\MIHC\768473\768473.yml` file 
+And the resulting `Y:\DATA\SARDANA\MIHC\768473\768473.yml` file
 
 ```yaml
 input dir: Y:\DATA\SARDANA\MIHC\768473\RAW
@@ -153,7 +153,7 @@ palom-svs run -c "Y:\DATA\SARDANA\MIHC\768473\768473.yml"
 ```
 
 When the process is finished, a pyramidal OME-TIFF file will be generated along
-with PNG files showing the feature-based registration results and a log file. 
+with PNG files showing the feature-based registration results and a log file.
 
 ```
 Y:\DATA\SARDANA\MIHC\768473\RAW
@@ -199,7 +199,7 @@ c1rp = palom.color.PyramidHaxProcessor(c1r.pyramid, thumbnail_level=THUMBNAIL_LE
 c2rp = palom.color.PyramidHaxProcessor(c2r.pyramid, thumbnail_level=THUMBNAIL_LEVEL)
 
 c21l = palom.align.Aligner(
-    c1rp.get_processed_color(LEVEL), 
+    c1rp.get_processed_color(LEVEL),
     c2rp.get_processed_color(LEVEL),
     ref_thumbnail=c1rp.get_processed_color(THUMBNAIL_LEVEL).compute(),
     moving_thumbnail=c2rp.get_processed_color(THUMBNAIL_LEVEL).compute(),

palom/__init__.py

@@ -11,7 +11,7 @@
     align,
     pyramid,
     color,
-    
+
     # debugging
     block_affine,
     extract,

palom/align.py

@@ -93,12 +93,12 @@ def viz_shifts(shifts, grid_shape, dcenter=None, ax=None):
     cax = ax.inset_axes([1.04, 0.0, 0.02, 1])
     colorbar = plt.colorbar(im, cax=cax)
     colorbar.set_ticks(colorbar_ticks)
-    
+
     return ax
 
 
 def block_affine_matrices(mx, shifts):
-        
+
     def shift_affine_mx(mx, shift):
         y, x = shift
         mx_shift = np.eye(3)
@@ -155,7 +155,7 @@ def coarse_register_affine(self, **kwargs):
         self.coarse_affine_matrix = np.vstack(
             [affine_matrix, [0, 0, 1]]
         )
-    
+
     @property
     def affine_matrix(self):
         if not hasattr(self, 'coarse_affine_matrix'):
@@ -169,13 +169,13 @@ def affine_matrix(self):
             mx_moving
         )
         return affine_matrix
-    
+
     @property
     def tform(self):
         return skimage.transform.AffineTransform(
             matrix=self.affine_matrix
         )
-    
+
     def affine_transformed_moving_img(self, mxs=None):
         if mxs is None:
             mxs = self.affine_matrix
@@ -185,7 +185,7 @@ def affine_transformed_moving_img(self, mxs=None):
         return block_affine_transformed_moving_img(
             ref_img, moving_img, mxs
         )
-    
+
     def compute_shifts(self, pcc_kwargs=None):
         logger.info(f"Computing block-wise shifts")
         ref_img = self.ref_img
@@ -212,7 +212,7 @@ def constrain_shifts(self):
             self.original_shifts,
             self.grid_shape
         )
-    
+
     @property
     def block_affine_matrices(self):
         mx = self.affine_matrix
@@ -226,7 +226,7 @@ def block_affine_matrices_da(self):
             self.grid_shape
         )
 
-    def overlay_grid(self, ax=None): 
+    def overlay_grid(self, ax=None):
         import matplotlib.pyplot as plt
         img = self.ref_thumbnail
         img = skimage.exposure.rescale_intensity(img, out_range=np.uint16)
@@ -249,7 +249,7 @@ def overlay_grid(self, ax=None):
         # checkerboard pattern
         ax.imshow(np.indices(shape).sum(axis=0) % 2, cmap='cool', alpha=0.2)
         return grid
-    
+
     def plot_shifts(self):
         import matplotlib.pyplot as plt
         fig, axs = plt.subplots(1, 2, sharex=True, sharey=True)
@@ -271,14 +271,14 @@ def get_aligner(
         )
     if thumbnail_level1 <= -1: thumbnail_level1 += len(reader1.pyramid)
     if thumbnail_level2 <= -1: thumbnail_level2 += len(reader2.pyramid)
-    return Aligner( 
-        reader1.read_level_channels(level1, channel1),  
-        reader2.read_level_channels(level2, channel2), 
-        reader1.read_level_channels(thumbnail_level1, channel1), 
-        reader2.read_level_channels(thumbnail_level2, channel2), 
-        reader1.level_downsamples[thumbnail_level1] / reader1.level_downsamples[level1], 
-        reader2.level_downsamples[thumbnail_level2] / reader2.level_downsamples[level2] 
-    ) 
+    return Aligner(
+        reader1.read_level_channels(level1, channel1), 
+        reader2.read_level_channels(level2, channel2),
+        reader1.read_level_channels(thumbnail_level1, channel1),
+        reader2.read_level_channels(thumbnail_level2, channel2),
+        reader1.level_downsamples[thumbnail_level1] / reader1.level_downsamples[level1],
+        reader2.level_downsamples[thumbnail_level2] / reader2.level_downsamples[level2]
+    )
 
 
 def match_thumbnail_level(readers):

palom/block_affine.py

@@ -30,13 +30,13 @@ def block_affine_dask(
 
 
 def block_affine(
-    position, block_shape, 
+    position, block_shape,
     transformation, src_img,
     fill_empty=0, multichannel=False,
     is_mask=False
 ):
     assert np.min(block_shape) >= 0, (
-        f'block_shape {block_shape} is invalid' 
+        f'block_shape {block_shape} is invalid'
     )
     if multichannel:
         assert np.min(block_shape) == block_shape[0], (
@@ -68,7 +68,7 @@ def block_affine(
     x0_src, y0_src = np.floor(
         np.clip(inversed_corners.min(axis=0), 0, None)
     ).astype(int)
-    
+
     if multichannel:
         src_img_block = src_img[:, y0_src:y1_src, x0_src:x1_src]
         src_img_block = np.moveaxis(src_img_block, 0, 2)

palom/cli/align_he.py

@@ -42,16 +42,16 @@ def align_he(
     aligner.coarse_register_affine(n_keypoints=5000, detect_flip_rotate=True)
     plt.gcf().suptitle(f"{p2.name} (coarse alignment)", fontsize=8)
     plt.gca().set_title(f"{p1.name} - {p2.name}", fontsize=6)
-    
+
     if viz_coarse_napari:
         _ = viz_coarse(r1, r2, LEVEL, LEVEL, channel1, channel2, aligner.affine_matrix)
 
     if not only_coarse:
         aligner.ref_img = r1.read_level_channels(LEVEL, channel1)
         aligner.moving_img = r2.read_level_channels(LEVEL, channel2)
-        
+
         aligner.compute_shifts()
-        
+
         fig = aligner.plot_shifts()
         fig.suptitle(f"{p2.name} (block shift distance)", fontsize=8)
         fig.axes[0].set_title(p1.name, fontsize=6)
@@ -60,9 +60,9 @@ def align_he(
 
     set_matplotlib_font(font_size=8)
     save_all_figs(out_dir=out_dir / 'qc', format='png')
-    
+
     if not only_qc:
-        mx = aligner.affine_matrix 
+        mx = aligner.affine_matrix
         if not only_coarse:
             mx = aligner.block_affine_matrices_da
         mosaic = palom.align.block_affine_transformed_moving_img(
@@ -84,7 +84,7 @@ def viz_coarse(r1, r2, level1, level2, channel1, channel2, mx):
     try:
         import napari
     except ImportError:
-        return 
+        return
     import dask.array as da
     v = napari.Viewer()
     is_bf1 = palom.img_util.is_brightfield_img(r1.pyramid[-1][channel1])
@@ -139,7 +139,7 @@ def save_all_figs(dpi=300, format='pdf', out_dir=None):
         try: import napari
         except ImportError: print("napari is not installed")
         else: napari.run()
-    
+
     '''
     Example 1: inspect coarse alignment using napari
     python align_he.py \
@@ -154,6 +154,6 @@ def save_all_figs(dpi=300, format='pdf', out_dir=None):
         "X:\crc-scans\histowiz scans\20230105-orion_2_cycles\22199$P54_33_HE$US$SCAN$OR$001 _104050.svs" \
         "X:\crc-scans\histowiz scans\20230105-orion_2_cycles\test" \
         --px_size1 0.325
-    
+   
     '''
 

palom/cli/flow.py

@@ -61,7 +61,7 @@ def optical_flow(
     if mask is None:
         mask = np.ones(mask_shape, dtype=bool)
     assert mask.shape == mask_shape
-    
+
     def func(
         p1, p2, ch1, ch2, mask,
         block_info=None
@@ -74,7 +74,7 @@ def func(
             slice(*np.ceil(np.divide(cloc, block_size)).astype(int))
         ]
         return block_optical_flow(chunk1, chunk2, block_size, mask=chunk_mask)
-    
+
     shifts = da.map_blocks(
         func,
         p1=p1, p2=p2, ch1=ch1, ch2=ch2, mask=mask,
@@ -104,12 +104,12 @@ def block_optical_flow(
     wv_img1 = skimage.util.view_as_windows(img1, block_shape, block_shape)
     wv_img2 = skimage.util.view_as_windows(img2, block_shape, block_shape)
     h, w = wv_img1.shape[:2]
-    
+
     wv_mask = np.ones((h, w, 1, 1), dtype=bool)
     if mask is not None:
         wv_mask = mask[..., np.newaxis, np.newaxis]
         wv_mask = wv_mask[..., :h, :w]
-    
+
     out = np.zeros((3, h, w), dtype=np.float32)
     product_func = itertools.product
     if show_progress:
@@ -158,7 +158,7 @@ def compose_thumbnail(p1, p2, ch1, ch2, log_intensity=True):
     rimg2 = skimage.exposure.match_histograms(rimg2, rimg1)
     out = np.array([rimg1, rimg2, rimg1])
     return out
- 
+
 
 def plot_legend(
     shifts, max_radius, plot_scatter, plot_kde,
@@ -252,7 +252,7 @@ def process_img_channel_pair(
     mask = None
     if compute_mask:
         mask = reader_block_mask(reader, block_size)
-    
+
     num_cpus = dask.system.cpu_count()
     if num_workers > num_cpus:
         num_workers =num_cpus
@@ -309,7 +309,7 @@ def process_img_channel_pair(
 
         for ax in fig.get_axes():
             ax.set_anchor('N')
-        
+
         plt.tight_layout()
         out_dir = img_path.parent / 'qc'
         out_dir.mkdir(exist_ok=True)
@@ -318,7 +318,7 @@ def process_img_channel_pair(
             bbox_inches='tight', dpi=144
         )
         figures.append(fig)
-    
+
     if as_script: return
     return all_shifts, figures
 
@@ -354,15 +354,15 @@ def process_img_channel_pair(
         -a, --as_script=AS_SCRIPT
             Default: True
 
-    --- 
-    
+    ---
+   
     NOTE: OTHER_CHANNELS is a list of integers, use [1] to indicate the
     second channel and [1,2,3] (do not include space) for second, third and
     fourth channels.
 
     Ref https://google.github.io/python-fire/guide/#argument-parsing
-    
-    Examples 
+   
+    Examples
 
     python flow.py \
         "Z:\RareCyte-S3\P54_CRCstudy_Bridge\S32-Tonsil-P54_Strip_P76.ome.tif" \

palom/cli/helper.py

@@ -11,7 +11,7 @@ def main(argv=sys.argv):
             'Generate configuration yaml file for palom-svs run'
         )
     )
-    
+
     parser.add_argument(
         '-i',
         metavar='input-dir',
@@ -36,9 +36,9 @@ def main(argv=sys.argv):
         help='full path to the resulting configuration yaml file',
         required=True
     )
-    
+
     args = parser.parse_args(argv[1:])
-    
+
     if len(argv) == 1:
         parser.print_help()
         return 0
@@ -68,7 +68,7 @@ def main(argv=sys.argv):
     )
 
     channel_names = [
-        '-'.join(p.name.split('_')[-2:][::-1]).replace('.svs', '') 
+        '-'.join(p.name.split('_')[-2:][::-1]).replace('.svs', '')
         for p in ([ref_slide] + svs_paths)
     ]
 

palom/cli/schema/svs-config-schema.yml

@@ -31,7 +31,7 @@ image collection: any(include('bright-field image'), include('fluorescent image'
 
 _image_base: &_image_base
     # Filename or the remaining path to the imaging data relative to the input
-    # dir field 
+    # dir field
     filename: str()
     # [optional but recommended]
     # Channel name in the output ome-tiff
@@ -43,7 +43,7 @@ bright-field image:
     channel names: list(str(), min=1, max=3, required=False)
     # Output color mode, currently the following 4 modes are available
     output mode: enum('aec', 'hematoxylin', 'color', 'grayscale', 'dab')
-  
+
 fluorescent image:
     <<: *_image_base
     output mode: str(equals='multichannel')