enabling data validation for the remaining methods

Author: dkazanc

httomolibgpu/misc/corr.py

@@ -36,7 +36,7 @@
 else:
     load_cuda_module = Mock()
 
-from httomolibgpu.misc.supp_func import _naninfs_check, _zeros_check
+from httomolibgpu.misc.supp_func import data_checker
 
 __all__ = [
     "median_filter",
@@ -82,19 +82,7 @@ def median_filter(
     else:
         raise ValueError("The input array must be a 3D array")
 
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "median_filter"
-
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data = data_checker(data, verbosity=True, method_name="median_filter_or_remove_outlier")
 
     if kernel_size not in [3, 5, 7, 9, 11, 13]:
         raise ValueError("Please select a correct kernel size: 3, 5, 7, 9, 11, 13")

httomolibgpu/misc/denoise.py

@@ -28,10 +28,9 @@
 cp = cupywrapper.cp
 cupy_run = cupywrapper.cupy_run
 
-from numpy import float32
 from unittest.mock import Mock
 
-from httomolibgpu.misc.supp_func import _naninfs_check, _zeros_check
+from httomolibgpu.misc.supp_func import data_checker
 
 if cupy_run:
     from ccpi.filters.regularisersCuPy import ROF_TV, PD_TV
@@ -82,19 +81,8 @@ def total_variation_ROF(
     ValueError
         If the input array is not float32 data type.
     """
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "total_variation_ROF"
 
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data = data_checker(data,verbosity=True,method_name="total_variation_ROF")
 
     return ROF_TV(
         data, regularisation_parameter, iterations, time_marching_parameter, gpu_id
@@ -140,19 +128,8 @@ def total_variation_PD(
     ValueError
         If the input array is not float32 data type.
     """
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "total_variation_PD"
 
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data_checker(data,verbosity=True,method_name="total_variation_PD")
 
     methodTV = 0
     if not isotropic:

httomolibgpu/misc/morph.py

@@ -35,7 +35,7 @@
 
 from typing import Literal
 
-from httomolibgpu.misc.supp_func import _naninfs_check, _zeros_check
+from httomolibgpu.misc.supp_func import data_checker
 
 __all__ = [
     "sino_360_to_180",
@@ -68,19 +68,7 @@ def sino_360_to_180(
     if data.ndim != 3:
         raise ValueError("only 3D data is supported")
 
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "sino_360_to_180"
-
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data = data_checker(data, verbosity=True, method_name="sino_360_to_180")
 
     dx, dy, dz = data.shape
 
@@ -152,19 +140,7 @@ def data_resampler(
         data = cp.expand_dims(data, 1)
         axis = 1
 
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "data_resampler"
-
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data = data_checker(data, verbosity=True, method_name="data_resampler")
 
     N, M, Z = cp.shape(data)
 

httomolibgpu/misc/rescale.py

@@ -28,7 +28,7 @@
 
 from typing import Literal, Optional, Tuple, Union
 
-from httomolibgpu.misc.supp_func import _naninfs_check, _zeros_check
+from httomolibgpu.misc.supp_func import data_checker
 
 __all__ = [
     "rescale_to_int",
@@ -80,19 +80,7 @@ def rescale_to_int(
     else:
         output_dtype = np.uint32
 
-    verbosity_enabled = True  # printing the data-related warnings
-    method_name = "rescale_to_int"
-
-    data = _naninfs_check(
-        data, correction=True, verbosity=verbosity_enabled, method_name=method_name
-    )
-
-    _zeros_check(
-        data,
-        verbosity=verbosity_enabled,
-        percentage_threshold=50,
-        method_name=method_name,
-    )
+    data = data_checker(data, verbosity=True, method_name="rescale_to_int")
 
     if cupy_run:
         xp = cp.get_array_module(data)

httomolibgpu/prep/alignment.py

@@ -35,6 +35,8 @@
 
 from typing import Dict, List, Tuple
 
+from httomolibgpu.misc.supp_func import data_checker
+
 __all__ = [
     "distortion_correction_proj_discorpy",
 ]
@@ -86,6 +88,8 @@ def distortion_correction_proj_discorpy(
     if len(data.shape) == 2:
         data = cp.expand_dims(data, axis=0)
 
+    data = data_checker(data, verbosity=True, method_name="distortion_correction_proj_discorpy")        
+
     # Get info from metadata txt file
     xcenter, ycenter, list_fact = _load_metadata_txt(metadata_path)
 

httomolibgpu/prep/normalize.py

@@ -36,6 +36,8 @@
 from numpy import float32
 from typing import Tuple
 
+from httomolibgpu.misc.supp_func import data_checker
+
 __all__ = ["normalize"]
 
 
@@ -80,7 +82,7 @@ def normalize(
     cp.ndarray
         Normalised 3D tomographic data as a CuPy array.
     """
-    _check_valid_input(data, flats, darks)
+    _check_valid_input_normalise(data, flats, darks)
 
     dark0 = cp.empty(darks.shape[1:], dtype=float32)
     flat0 = cp.empty(flats.shape[1:], dtype=float32)
@@ -128,7 +130,7 @@ def normalize(
     return out
 
 
-def _check_valid_input(data, flats, darks) -> None:
+def _check_valid_input_normalise(data, flats, darks) -> None:
     """Helper function to check the validity of inputs to normalisation functions"""
     if data.ndim != 3:
         raise ValueError("Input data must be a 3D stack of projections")
@@ -143,3 +145,7 @@ def _check_valid_input(data, flats, darks) -> None:
         flats = flats[cp.newaxis, :, :]
     if darks.ndim == 2:
         darks = darks[cp.newaxis, :, :]
+    
+    data_checker(data,verbosity=True,method_name="normalize_data")
+    data_checker(flats,verbosity=True,method_name="normalize_flats")
+    data_checker(darks,verbosity=True,method_name="normalize_darks")

httomolibgpu/prep/phase.py

@@ -41,6 +41,8 @@
 from typing import Tuple
 import math
 
+from httomolibgpu.misc.supp_func import data_checker
+
 __all__ = [
     "paganin_filter_savu",
     "paganin_filter_tomopy",
@@ -105,6 +107,8 @@ def paganin_filter_savu(
             " please provide a stack of 2D projections."
         )
 
+    data = data_checker(data, verbosity=True, method_name="paganin_filter_savu")
+
     # Setup various values for the filter
     _, height, width = data.shape
     micron = 1e-6
@@ -296,6 +300,8 @@ def paganin_filter_tomopy(
             f"Invalid number of dimensions in data: {tomo.ndim},"
             " please provide a stack of 2D projections."
         )
+    
+    tomo = data_checker(tomo, verbosity=True, method_name="paganin_filter_tomopy")
 
     dz_orig, dy_orig, dx_orig = tomo.shape
 

httomolibgpu/prep/stripe.py

@@ -43,6 +43,8 @@
 
 from typing import Union
 
+from httomolibgpu.misc.supp_func import data_checker
+
 __all__ = [
     "remove_stripe_based_sorting",
     "remove_stripe_ti",
@@ -80,6 +82,9 @@ def remove_stripe_based_sorting(
         Corrected 3D tomographic data as a CuPy or NumPy array.
 
     """
+
+    data = data_checker(data, verbosity=True, method_name="remove_stripe_based_sorting")
+
     if size is None:
         if data.shape[2] > 2000:
             size = 21
@@ -134,7 +139,13 @@ def remove_stripe_ti(
     ndarray
         3D array of de-striped projections.
     """
-    # TODO: detector dimensions must be even otherwise error
+    data = data_checker(data, verbosity=True, method_name="remove_stripe_ti")
+
+    _, _, dx_orig = data.shape
+    if (dx_orig % 2) != 0:
+        # the horizontal detector size is odd, data needs to be padded/cropped, for now raising the error
+        raise ValueError("The horizontal detector size must be even")    
+
     gamma = beta * ((1 - beta) / (1 + beta)) ** cp.abs(
         cp.fft.fftfreq(data.shape[-1]) * data.shape[-1]
     )
@@ -201,6 +212,8 @@ def remove_all_stripe(
         Corrected 3D tomographic data as a CuPy or NumPy array.
 
     """
+    data = data_checker(data, verbosity=True, method_name="remove_all_stripe")
+
     matindex = _create_matindex(data.shape[2], data.shape[0])
     for m in range(data.shape[1]):
         sino = data[:, m, :]
@@ -372,9 +385,10 @@ def raven_filter(
     ValueError
         If the input array is not three dimensional.
     """
-
     if data.dtype != cp.float32:
         raise ValueError("The input data should be float32 data type")
+    
+    data = data_checker(data, verbosity=True, method_name="raven_filter")
 
     # Padding of the sinogram
     data = cp.pad(data, ((pad_y, pad_y), (0, 0), (pad_x, pad_x)), mode=pad_method)

httomolibgpu/recon/algorithm.py

@@ -40,6 +40,8 @@
 from numpy import float32, complex64
 from typing import Optional, Type
 
+from httomolibgpu.misc.supp_func import data_checker
+
 
 __all__ = [
     "FBP2d_astra",
@@ -103,6 +105,8 @@ def FBP2d_astra(
     np.ndarray
         The FBP reconstructed volume as a numpy array.
     """
+    data = data_checker(data, verbosity=True, method_name="FBP2d_astra")
+
     data_shape = np.shape(data)
     if recon_size is None:
         recon_size = data_shape[2]
@@ -175,6 +179,8 @@ def FBP3d_tomobar(
     cp.ndarray
         FBP reconstructed volume as a CuPy array.
     """
+    data = data_checker(data, verbosity=True, method_name="FBP3d_tomobar")
+
     RecToolsCP = _instantiate_direct_recon_class(
         data, angles, center, recon_size, gpu_id
     )
@@ -227,6 +233,9 @@ def LPRec3d_tomobar(
     cp.ndarray
         The Log-polar Fourier reconstructed volume as a CuPy array.
     """
+
+    data = data_checker(data, verbosity=True, method_name="LPRec3d_tomobar")
+
     RecToolsCP = _instantiate_direct_recon_class(data, angles, center, recon_size, 0)
 
     reconstruction = RecToolsCP.FOURIER_INV(
@@ -281,6 +290,8 @@ def SIRT3d_tomobar(
     cp.ndarray
         The SIRT reconstructed volume as a CuPy array.
     """
+    data = data_checker(data, verbosity=True, method_name="SIRT3d_tomobar")
+
     RecToolsCP = _instantiate_iterative_recon_class(
         data,
         angles,
@@ -346,6 +357,8 @@ def CGLS3d_tomobar(
     cp.ndarray
         The CGLS reconstructed volume as a CuPy array.
     """
+    data = data_checker(data, verbosity=True, method_name="CGLS3d_tomobar")
+
     RecToolsCP = _instantiate_iterative_recon_class(
         data, angles, center, recon_size, gpu_id, datafidelity="LS"
     )