Improve image preprocessing prints

foa3d/output.py

@@ -43,7 +43,6 @@ def create_save_dirs(img_path, img_name, cli_args, is_fiber=False):
     base_out_dir = path.join(out_path, time_stamp + '_' + img_name)
     save_dir_lst = list()
     if not path.isdir(base_out_dir):
-        print("Creating directory")
         makedirs(base_out_dir)
 
     # create Frangi filter output subdirectory

foa3d/preprocessing.py

@@ -34,35 +34,41 @@ def config_anisotropy_correction(px_sz, psf_fwhm):
         new isotropic pixel size [μm]
     """
 
-    # print preprocessing heading
-    print_prepro_heading()
-
     # set the isotropic pixel resolution equal to the z-sampling step
     px_sz_iso = px_sz[0] * np.ones(shape=(3,))
 
-    # adjust PSF anisotropy via lateral Gaussian blurring
-    if not np.all(psf_fwhm == psf_fwhm[0]):
+    # detect preprocessing requirement
+    cndt_1 = not np.all(psf_fwhm == psf_fwhm[0])
+    cndt_2 = np.any(px_sz != 1.0)
+    smooth_sigma = None
+    if cndt_1 or cndt_2:
 
-        # estimate the PSF variance from input FWHM values [μm^2]
-        psf_var = np.square(fwhm_to_sigma(psf_fwhm))
+        # print preprocessing heading
+        print_prepro_heading()
 
-        # estimate the in-plane filter variance [μm^2]
-        gauss_var = np.array([0, psf_var[0] - psf_var[1], psf_var[0] - psf_var[2]])
+        # adjust PSF anisotropy via lateral Gaussian blurring
+        if cndt_1:
 
-        # ...and the corresponding standard deviation [px]
-        smooth_sigma = np.divide(np.sqrt(gauss_var), px_sz)
+            # estimate the PSF variance from input FWHM values [μm^2]
+            psf_var = np.square(fwhm_to_sigma(psf_fwhm))
 
-        # print preprocessing info
-        smooth_sigma_um = np.multiply(smooth_sigma, px_sz)
-        print_blur(smooth_sigma_um)
+            # estimate the in-plane filter variance [μm^2]
+            gauss_var = np.array([0, psf_var[0] - psf_var[1], psf_var[0] - psf_var[2]])
 
-    # (no blurring)
-    else:
-        print("\n")
-        smooth_sigma = None
+            # ...and the corresponding standard deviation [px]
+            smooth_sigma = np.divide(np.sqrt(gauss_var), px_sz)
+
+            # print preprocessing info
+            smooth_sigma_um = np.multiply(smooth_sigma, px_sz)
+            print_blur(smooth_sigma_um, psf_fwhm)
 
-    # print pixel resize info
-    print_new_res(px_sz_iso, psf_fwhm)
+        # print pixel resize info
+        if cndt_2:
+            print_new_res(px_sz_iso)
+
+    # skip line
+    else:
+        print()
 
     return smooth_sigma, px_sz_iso
 

foa3d/printing.py

@@ -116,7 +116,7 @@ def print_analysis_time(start_time):
     print("\nVolume image analyzed in: {0} min {1:3.1f} s\n".format(mins, secs))
 
 
-def print_blur(smooth_sigma_um):
+def print_blur(smooth_sigma_um, psf_fwhm):
     """
     Print gaussian lowpass filter standard deviation.
 
@@ -126,13 +126,16 @@ def print_blur(smooth_sigma_um):
         3D standard deviation of the low-pass Gaussian filter [μm]
         (resolution anisotropy correction)
 
+    psf_fwhm: numpy.ndarray (shape=(3,), dtype=float)
+        3D FWHM of the PSF [μm]
+
     Returns
     -------
     None
     """
-    print("\n                              Z      Y      X")
     print("Gaussian blur \u03C3      [μm]: ({0:.3f}, {1:.3f}, {2:.3f})"
-          .format(smooth_sigma_um[0], smooth_sigma_um[1], smooth_sigma_um[2]), end='\r')
+          .format(smooth_sigma_um[0], smooth_sigma_um[1], smooth_sigma_um[2]))
+    print("Adjusted PSF FWHM    [μm]: ({0:.3f}, {0:.3f}, {0:.3f})\n".format(psf_fwhm[0]))
 
 
 def print_import_time(start_time):
@@ -193,6 +196,7 @@ def print_prepro_heading():
     None
     """
     print(color_text(0, 191, 255, "\n\nMicroscopy Volume Image Preprocessing"))
+    print("\n                              Z      Y      X")
 
 
 def print_native_res(px_size, psf_fwhm):
@@ -215,7 +219,7 @@ def print_native_res(px_size, psf_fwhm):
     print("PSF FWHM             [μm]: ({0:.3f}, {1:.3f}, {2:.3f})".format(psf_fwhm[0], psf_fwhm[1], psf_fwhm[2]))
 
 
-def print_new_res(px_sz_iso, psf_fwhm):
+def print_new_res(px_sz_iso):
     """
     Print adjusted isotropic spatial resolution.
 
@@ -224,15 +228,11 @@ def print_new_res(px_sz_iso, psf_fwhm):
     px_sz_iso: numpy.ndarray (shape=(3,), dtype=float)
         new isotropic pixel size [μm]
 
-    psf_fwhm: numpy.ndarray (shape=(3,), dtype=float)
-        3D FWHM of the PSF [μm]
-
     Returns
     -------
     None
     """
-    print("\nAdjusted pixel size  [μm]: ({0:.3f}, {1:.3f}, {2:.3f})".format(px_sz_iso[0], px_sz_iso[1], px_sz_iso[2]))
-    print("Adjusted PSF FWHM    [μm]: ({0:.3f}, {0:.3f}, {0:.3f})\n".format(psf_fwhm[0]))
+    print("Adjusted pixel size  [μm]: ({0:.3f}, {1:.3f}, {2:.3f})\n".format(px_sz_iso[0], px_sz_iso[1], px_sz_iso[2]))
 
 
 def print_slicing_info(image_shape_um, slice_shape_um, tot_slice_num, px_size, image_item_size):