updates to tests and functions using new data checker

Author: dkazanc

httomolibgpu/misc/corr.py

@@ -41,6 +41,7 @@
     "remove_outlier",
 ]
 
+
 def median_filter(
     data: cp.ndarray,
     kernel_size: int = 3,

httomolibgpu/misc/morph.py

@@ -40,6 +40,7 @@
     "data_resampler",
 ]
 
+
 def sino_360_to_180(
     data: cp.ndarray, overlap: float = 0, side: Literal["left", "right"] = "left"
 ) -> cp.ndarray:

httomolibgpu/misc/utils.py

@@ -39,7 +39,13 @@
 ]
 
 
-def data_checker(data: cp.ndarray, infsnans_correct: bool= True, zeros_warning: bool = False, data_to_method_name: Optional[str] = None, verbosity: bool = True) -> cp.ndarray:
+def data_checker(
+    data: cp.ndarray,
+    infsnans_correct: bool = True,
+    zeros_warning: bool = False,
+    data_to_method_name: Optional[str] = None,
+    verbosity: bool = True,
+) -> cp.ndarray:
     """Function that performs checks on input data to ensure its validity, performs corrections and prints the warnings.
     Currently it checks for the presence of Infs and NaNs in the data and corrects them.
 
@@ -54,7 +60,7 @@ def data_checker(data: cp.ndarray, infsnans_correct: bool= True, zeros_warning:
     verbosity : bool
         Print the warnings.
     data_to_method_name : str, optional.
-        Method's name for which the tested data is intended. This is for printing purposes when the method runs in HTTomo.
+        Method's name the output of which is tested. This is tailored for printing purposes when the method runs in HTTomo.
 
     Returns
     -------
@@ -67,11 +73,12 @@ def data_checker(data: cp.ndarray, infsnans_correct: bool= True, zeros_warning:
         )
 
     if infsnans_correct:
-        data = __naninfs_check(data, verbosity=verbosity, method_name=data_to_method_name)\
-    
+        data = __naninfs_check(
+            data, verbosity=verbosity, method_name=data_to_method_name
+        )
     # TODO
     # if zeros_warning:
-        #__zeros_check(data, verbosity=verbosity, percentage_threshold = 50, method_name=data_to_method_name)
+    # __zeros_check(data, verbosity=verbosity, percentage_threshold = 50, method_name=data_to_method_name)
 
     return data
 
@@ -91,7 +98,7 @@ def __naninfs_check(
     verbosity : bool
         If enabled, then the printing of the warning happens when data contains infs or nans
     method_name : str, optional.
-        Method's name for which input data is tested.
+        Method's name for which the output data is tested.
 
     Returns
     -------
@@ -132,8 +139,8 @@ def __naninfs_check(
     if present_nans_infs_b:
         if verbosity:
             print(
-                f"Warning!!! Input data to method: {method_name} contains Inf's or/and NaN's. This will be corrected but it is recommended to check the validity of input to the method."
+                "Warning! Output data of the \033[31m{}\033[0m method contains Inf's or/and NaN's. Corrected to zeros.".format(
+                    method_name
+                )
             )
-
     return data
-

httomolibgpu/prep/stripe.py

@@ -386,7 +386,6 @@ def raven_filter(
     if data.dtype != cp.float32:
         raise ValueError("The input data should be float32 data type")
 
-
     # Padding of the sinogram
     data = cp.pad(data, ((pad_y, pad_y), (0, 0), (pad_x, pad_x)), mode=pad_method)
 

httomolibgpu/recon/rotation.py

@@ -110,7 +110,12 @@ def find_center_vo(
         data = cp.expand_dims(data, 1)
         ind = 0
 
-    data = data_checker(data, infsnans_correct=True, zeros_warning = False, data_to_method_name="find_center_vo")
+    data = data_checker(
+        data,
+        infsnans_correct=True,
+        zeros_warning=False,
+        data_to_method_name="find_center_vo",
+    )
 
     angles_tot, detY_size, detX_size = data.shape
 
@@ -459,7 +464,12 @@ def find_center_360(
     if data.ndim != 3:
         raise ValueError("A 3D array must be provided")
 
-    data = data_checker(data, infsnans_correct=True, zeros_warning = False, data_to_method_name="find_center_360")
+    data = data_checker(
+        data,
+        infsnans_correct=True,
+        zeros_warning=False,
+        data_to_method_name="find_center_360",
+    )
 
     # this method works with a 360-degree sinogram.
     if ind is None:
@@ -740,6 +750,7 @@ def _calculate_curvature(list_metric):
 
     return curvature, np.float32(min_pos)
 
+
 ## %%%%%%%%%%%%%%%%%%%%%%find_center_pc%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 def find_center_pc(
     proj1: cp.ndarray,
@@ -771,8 +782,18 @@ def find_center_pc(
     np.float32
         Rotation axis location.
     """
-    proj1 = data_checker(proj1, infsnans_correct=True, zeros_warning = False, data_to_method_name="find_center_pc")
-    proj2 = data_checker(proj2, infsnans_correct=True, zeros_warning = False, data_to_method_name="find_center_pc")    
+    proj1 = data_checker(
+        proj1,
+        infsnans_correct=True,
+        zeros_warning=False,
+        data_to_method_name="find_center_pc",
+    )
+    proj2 = data_checker(
+        proj2,
+        infsnans_correct=True,
+        zeros_warning=False,
+        data_to_method_name="find_center_pc",
+    )
 
     imgshift = 0.0 if rotc_guess is None else rotc_guess - (proj1.shape[1] - 1.0) / 2.0