Use pathlib

stpt_pipeline/main.py

 import logging
 from os import listdir
+from pathlib import Path
 
 import numpy as np
 from dask import delayed  # noqa: F401
@@ -65,21 +66,21 @@ def list_directories(root_dir):
         if this_file.find('4t1') > -1:
             if this_file.find('.txt') > -1:
                 continue
-            dirs.append(root_dir + '/' + this_file + '/')
+            dirs.append(root_dir / this_file)
     dirs.sort()
     return dirs
 
 
-def main(*, root_dir: str, flat_file: str, output_dir: str):
+def main(*, root_dir: Path, flat_file: Path, output_dir: Path):
     """[summary]
 
     Parameters
     ----------
-    root_dir : str
+    root_dir : Path
         [description]
-    flat_file : str
+    flat_file : Path
         [description]
-    output_dir : str
+    output_dir : Path
         [description]
     """
     log.info('Reading flatfield %s', flat_file)
@@ -92,7 +93,7 @@ def main(*, root_dir: str, flat_file: str, output_dir: str):
         log.info('Processing directory %s', this_dir)
         # read mosaic file, get delta in microns
         mosaic_file = get_mosaic_file(this_dir)
-        dx, dy, lx, ly = read_mosaicifile_stpt(this_dir + mosaic_file)
+        dx, dy, lx, ly = read_mosaicifile_stpt(this_dir / mosaic_file)
         delta_x, delta_y = find_delta(dx, dy)
         log.debug('delta_x : %s , delta_y: %s', delta_x, delta_y)
         # dx0,dy0 are just the coordinates of each image

stpt_pipeline/mosaic_functions.py

@@ -2,7 +2,7 @@ from os import listdir
 
 import numpy as np
 
-from imaxt_image.external import tifffile as tf
+from imaxt_image.image import TiffImage
 
 
 def find_delta(dx, dy):
@@ -143,25 +143,5 @@ def get_img_cube(
         (channel == channel_to_use)
         & ((optical_slice - np.min(optical_slice) + 1) == slice_to_use)
     )[0]
-    im_t = [tf.imread(root_dir + t).astype('float32') for t in imgs[ii]]
-    #
-    return np.array(im_t)
-
-
-def imread(img_name):
-    """[summary]
-
-    Parameters
-    ----------
-    img_name : [type]
-        [description]
-
-    Returns
-    -------
-    [type]
-        [description]
-    """
-    # this is just for convenience in case we change tiff library
-    im_t = tf.imread(img_name).astype('float32')
-    #
-    return im_t
+    im_t = [TiffImage(root_dir / t).asarray() for t in imgs[ii]]
+    return np.array(im_t).astype('float32')

stpt_pipeline/schema.py

 import voluptuous as vo
+from pathlib import Path
 
 schema = vo.Schema(
     {
-        vo.Required('root_dir'): str,
-        vo.Required('output_dir'): str,
-        vo.Required('flat_file'): str,
+        vo.Required('root_dir'): vo.Coerce(Path),
+        vo.Required('output_dir'): vo.Coerce(Path),
+        vo.Required('flat_file'): vo.Coerce(Path),
     }
 )