[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

scripts/reduce_CG1D.py

@@ -7,7 +7,11 @@
 from imars3d.backend import extract_info_from_path
 from imars3d.backend import substitute_template
 from imars3d.backend.autoredux import logger as logger_autoredux
-from imars3d.backend.workflow.engine import WorkflowEngineAuto, WorkflowEngineError, WorkflowEngineExitCodes
+from imars3d.backend.workflow.engine import (
+    WorkflowEngineAuto,
+    WorkflowEngineError,
+    WorkflowEngineExitCodes,
+)
 from imars3d.backend.util.functions import to_time_str
 
 # standard imports
@@ -49,7 +53,9 @@ def _find_template_config() -> Path:
     autored_dir = Path(__file__).parent
     path_to_file = autored_dir / template_name
     if not path_to_file.exists():
-        raise FileNotFoundError(f"Template {template_name} not found in directory {autored_dir}")
+        raise FileNotFoundError(
+            f"Template {template_name} not found in directory {autored_dir}"
+        )
     return path_to_file
 
 
@@ -130,7 +136,9 @@ def main(inputfile: Union[str, Path], outputdir: Union[str, Path]) -> int:
         log_file_handler.flush()
         root_logger.removeHandler(log_file_handler)
         log_file_handler.close()
-        shutil.move(log_file_path, radiographs_dir)  # move the log file to the radiographs directory
+        shutil.move(
+            log_file_path, radiographs_dir
+        )  # move the log file to the radiographs directory
     else:
         config_file_path = outputdir / f"{config_file_name}_{time_str}.json"
         save_config(config_dict, config_file_path)

src/imars3d/__init__.py

@@ -1,6 +1,13 @@
 """iMars3D: a Python package for neutron imaging and tomography reconstruction."""
 import logging
-from .backend import corrections, diagnostics, dataio, morph, preparation, reconstruction  # noqa: F401
+from .backend import (
+    corrections,
+    diagnostics,
+    dataio,
+    morph,
+    preparation,
+    reconstruction,
+)  # noqa: F401
 
 logging.getLogger("imars3d").setLevel(logging.INFO)
 try:

src/imars3d/backend/autoredux.py

@@ -37,7 +37,9 @@ def auto_reduction_ready(data_file: Union[str, Path]) -> bool:
     if match:
         image_type = match.groups()[0]
         if image_type in non_radiograph["dark-field"] + non_radiograph["open-beam"]:
-            logger.info("The input image is not a radiograph. It's assumed the scan is incomplete.")
+            logger.info(
+                "The input image is not a radiograph. It's assumed the scan is incomplete."
+            )
             return False
     else:
         logger.error("non-canonical data file path")
@@ -115,7 +117,9 @@ def extract_info_from_path(data_file: Union[str, Path]) -> dict:
     raw_position = 4
 
     extracted_data = Path(data_file).parts
-    assert extracted_data[0] == os.path.sep, f"Path {str(data_file)} is not an absolute path"
+    assert (
+        extracted_data[0] == os.path.sep
+    ), f"Path {str(data_file)} is not an absolute path"
 
     # Extract FACILITY, INSTRUMENT, and IPTS
     data_dict = {}
@@ -133,7 +137,9 @@ def extract_info_from_path(data_file: Union[str, Path]) -> dict:
     data_dict["radiograph"] = extracted_data[ct_position]
 
     # Extract PREPATH and SUBPATH
-    data_dict["prepath"] = os.path.sep.join(extracted_data[1 + raw_position : ct_position])
+    data_dict["prepath"] = os.path.sep.join(
+        extracted_data[1 + raw_position : ct_position]
+    )
     data_dict["subpath"] = os.path.sep.join(extracted_data[1 + ct_position : -1])
 
     logger.info("Extract information from data file path.")
@@ -167,8 +173,14 @@ def substitute_template(config: dict, values: dict) -> dict:
             "dcdir": str(pre_path / "df" / values["subpath"]),
         }
     )
-    assert {"facility", "instrument", "ipts", "name", "workingdir", "outputdir", "tasks"}.issubset(
-        set(config.keys())
-    ), "Config template dict is missing keys."
+    assert {
+        "facility",
+        "instrument",
+        "ipts",
+        "name",
+        "workingdir",
+        "outputdir",
+        "tasks",
+    }.issubset(set(config.keys())), "Config template dict is missing keys."
     template = Template(json.dumps(config))
     return json.loads(template.substitute(**values))

src/imars3d/backend/corrections/beam_hardening.py

@@ -8,7 +8,9 @@
 from multiprocessing.managers import SharedMemoryManager
 from functools import partial
 from tqdm.contrib.concurrent import process_map
-from algotom.prep.correction import beam_hardening_correction as algotom_beam_hardening_correction
+from algotom.prep.correction import (
+    beam_hardening_correction as algotom_beam_hardening_correction,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -74,11 +76,15 @@ def __call__(self, **params):
         logger.debug(f"max_worker={self.max_workers}")
 
         if params.arrays.ndim == 2:
-            return algotom_beam_hardening_correction(params.arrays, params.q, params.n, params.opt)
+            return algotom_beam_hardening_correction(
+                params.arrays, params.q, params.n, params.opt
+            )
         elif params.arrays.ndim == 3:
             with SharedMemoryManager() as smm:
                 shm = smm.SharedMemory(params.arrays.nbytes)
-                shm_arrays = np.ndarray(params.arrays.shape, dtype=params.arrays.dtype, buffer=shm.buf)
+                shm_arrays = np.ndarray(
+                    params.arrays.shape, dtype=params.arrays.dtype, buffer=shm.buf
+                )
                 np.copyto(shm_arrays, params.arrays)
                 # mp
                 kwargs = {
@@ -88,7 +94,12 @@ def __call__(self, **params):
                 if self.tqdm_class:
                     kwargs["tqdm_class"] = self.tqdm_class
                 rst = process_map(
-                    partial(algotom_beam_hardening_correction, q=params.q, n=params.n, opt=params.opt),
+                    partial(
+                        algotom_beam_hardening_correction,
+                        q=params.q,
+                        n=params.n,
+                        opt=params.opt,
+                    ),
                     [shm_arrays[i] for i in range(shm_arrays.shape[0])],
                     **kwargs,
                 )

src/imars3d/backend/corrections/denoise.py

@@ -110,7 +110,11 @@ def denoise_by_median(
 
 
 def denoise_by_bilateral(
-    arrays: np.ndarray, sigma_color: float = 0.02, sigma_spatial: float = 5.0, max_workers: int = 0, tqdm_class=None
+    arrays: np.ndarray,
+    sigma_color: float = 0.02,
+    sigma_spatial: float = 5.0,
+    max_workers: int = 0,
+    tqdm_class=None,
 ) -> np.ndarray:
     """
     Denoise the image stack with the bilateral filter.
@@ -159,7 +163,11 @@ def denoise_by_bilateral(
                 kwargs["tqdm_class"] = tqdm_class
 
             rst = process_map(
-                partial(denoise_by_bilateral_2d, sigma_color=sigma_color, sigma_spatial=sigma_spatial),
+                partial(
+                    denoise_by_bilateral_2d,
+                    sigma_color=sigma_color,
+                    sigma_spatial=sigma_spatial,
+                ),
                 [img for img in shm_arrays],
                 **kwargs,
             )
@@ -196,7 +204,9 @@ def denoise_by_bilateral_2d(
     logger.debug(f"denoise_by_bilateral_2d:array2d_max = {array2d_max}")
     _sigma_color = sigma_color / array2d_max
     array_2d /= array2d_max
-    array_2d = denoise_bilateral(array_2d, sigma_color=_sigma_color, sigma_spatial=sigma_spatial)
+    array_2d = denoise_bilateral(
+        array_2d, sigma_color=_sigma_color, sigma_spatial=sigma_spatial
+    )
     return array_2d * array2d_max
 
 

src/imars3d/backend/corrections/gamma_filter.py

@@ -41,7 +41,10 @@ class gamma_filter(param.ParameterizedFunction):
         corrected 3D array of images, the first dimension is the rotation angle omega
     """
 
-    arrays = param.Array(doc="3D array of images, the first dimension is the rotation angle omega", default=None)
+    arrays = param.Array(
+        doc="3D array of images, the first dimension is the rotation angle omega",
+        default=None,
+    )
     threshold = param.Integer(
         default=-1,
         doc="threshold for saturation, default is -1, which means using the internally defined threshold (see source code)",
@@ -90,13 +93,21 @@ def __call__(self, **params):
         try:
             saturation_intensity = np.iinfo(params.arrays.dtype).max
         except ValueError:
-            logger.warning("Switch to use standard uint16 threshold as given arrays are float type.")
+            logger.warning(
+                "Switch to use standard uint16 threshold as given arrays are float type."
+            )
             saturation_intensity = 65535
-        threshold = saturation_intensity - 5 if params.threshold == -1 else params.threshold
+        threshold = (
+            saturation_intensity - 5 if params.threshold == -1 else params.threshold
+        )
         logger.debug(f"threshold={threshold}")
 
         # NOTE: use 20% of the total dynamic range as the outlier detection criterion
-        diff_tomopy = 0.2 * saturation_intensity if params.diff_tomopy < 0.0 else params.diff_tomopy
+        diff_tomopy = (
+            0.2 * saturation_intensity
+            if params.diff_tomopy < 0.0
+            else params.diff_tomopy
+        )
         logger.debug(f"diff_tomopy={diff_tomopy}")
         # median filtering
         arrays_filtered = tomopy.remove_outlier(

src/imars3d/backend/corrections/intensity_fluctuation_correction.py

@@ -38,7 +38,10 @@ class intensity_fluctuation_correction(param.ParameterizedFunction):
         The corrected image/radiograph stack.
     """
 
-    ct = param.Array(doc="The image/radiograph stack to correct for beam intensity fluctuation.", default=None)
+    ct = param.Array(
+        doc="The image/radiograph stack to correct for beam intensity fluctuation.",
+        default=None,
+    )
     air_pixels = param.Integer(
         default=5,
         doc="Number of pixels at each boundary to calculate the scaling factor. When a negative number is given, the auto air region detection will be used instead of tomopy.",
@@ -66,12 +69,18 @@ def __call__(self, **params):
         self.max_workers = clamp_max_workers(params.max_workers)
         logger.debug(f"max_workers={self.max_workers}")
         corrected_array = self._intensity_fluctuation_correction(
-            params.ct, params.air_pixels, params.sigma, self.max_workers, params.tqdm_class
+            params.ct,
+            params.air_pixels,
+            params.sigma,
+            self.max_workers,
+            params.tqdm_class,
         )
         logger.info("FINISHED Executing Filter: Intensity Fluctuation Correction")
         return corrected_array
 
-    def _intensity_fluctuation_correction(self, ct, air_pixels, sigma, max_workers, tqdm_class):
+    def _intensity_fluctuation_correction(
+        self, ct, air_pixels, sigma, max_workers, tqdm_class
+    ):
         """Correct for intensity fluctuation in the radiograph."""
         # validation
         if ct.ndim not in (2, 3):
@@ -254,6 +263,10 @@ def __call__(self, **params):
     def _normalize_roi(self, ct, roi, max_workers):
         # sanity check
         if ct.ndim != 3:
-            raise ValueError("This correction can only be used for a stack, i.e. a 3D image.")
-        proj_norm_beam_fluctuation = tomopy.prep.normalize.normalize_roi(ct, roi=roi, ncore=max_workers)
+            raise ValueError(
+                "This correction can only be used for a stack, i.e. a 3D image."
+            )
+        proj_norm_beam_fluctuation = tomopy.prep.normalize.normalize_roi(
+            ct, roi=roi, ncore=max_workers
+        )
         return proj_norm_beam_fluctuation

src/imars3d/backend/corrections/ring_removal.py

@@ -67,7 +67,9 @@ class bm3d_ring_removal(param.ParameterizedFunction):
 
     arrays = param.Array(doc="Input radiograph stack.", default=None)
     # parameters passed to bm3dsr.extreme_streak_attenuation
-    extreme_streak_iterations = param.Integer(default=3, doc="Number of iterations for extreme streak attenuation.")
+    extreme_streak_iterations = param.Integer(
+        default=3, doc="Number of iterations for extreme streak attenuation."
+    )
     extreme_detect_lambda = param.Number(
         default=4.0,
         doc="Consider streaks which are stronger than lambda * local_std as extreme.",
@@ -117,8 +119,12 @@ class bm3d_ring_removal(param.ParameterizedFunction):
     def __call__(self, **params):
         """See class level documentation for help."""
         if not bm3dsr:
-            logger.warning("To use method, make sure to install bm3d_streak_removal package via pip.")
-            raise RuntimeError("BM3D suite not installed, please install with pip install bm3d_streak_removal")
+            logger.warning(
+                "To use method, make sure to install bm3d_streak_removal package via pip."
+            )
+            raise RuntimeError(
+                "BM3D suite not installed, please install with pip install bm3d_streak_removal"
+            )
         else:
             logger.info("Executing Filter: Remove Ring Artifact with BM3D")
         _ = self.instance(**params)
@@ -181,15 +187,22 @@ class remove_ring_artifact(param.ParameterizedFunction):
 
     arrays = param.Array(doc="Input radiograph stack.", default=None)
     kernel_size = param.Integer(
-        default=5, doc="The size of the kernel (moving window) during local smoothing with median filter."
+        default=5,
+        doc="The size of the kernel (moving window) during local smoothing with median filter.",
     )
     sub_division = param.Integer(
-        default=10, doc="Sub-dividing the sinogram into subsections (along rotation angle axis)."
+        default=10,
+        doc="Sub-dividing the sinogram into subsections (along rotation angle axis).",
     )
     correction_range = param.List(
-        default=[0.9, 1.1], doc="Multiplicative correction factor is capped within given range."
+        default=[0.9, 1.1],
+        doc="Multiplicative correction factor is capped within given range.",
+    )
+    max_workers = param.Integer(
+        default=0,
+        bounds=(0, None),
+        doc="Number of cores to use for parallel processing.",
     )
-    max_workers = param.Integer(default=0, bounds=(0, None), doc="Number of cores to use for parallel processing.")
     tqdm_class = param.ClassSelector(class_=object, doc="Progress bar to render with")
 
     def __call__(self, **params):
@@ -219,7 +232,9 @@ def _remove_ring_artifact(
     ) -> np.ndarray:
         # sanity check
         if arrays.ndim != 3:
-            raise ValueError("This correction can only be used for a stack, i.e. a 3D image.")
+            raise ValueError(
+                "This correction can only be used for a stack, i.e. a 3D image."
+            )
         # NOTE:
         # additional work is needed to avoid duplicating arrays in memory
         max_workers = clamp_max_workers(max_workers)
@@ -288,13 +303,16 @@ class remove_ring_artifact_Ketcham(param.ParameterizedFunction):
 
     sinogram = param.Array(doc="Input sinogram.", default=None)
     kernel_size = param.Integer(
-        default=5, doc="The size of the kernel (moving window) during local smoothing via median filter."
+        default=5,
+        doc="The size of the kernel (moving window) during local smoothing via median filter.",
     )
     sub_division = param.Integer(
-        default=10, doc="Sub-dividing the sinogram into subsections (along rotation angle axis)."
+        default=10,
+        doc="Sub-dividing the sinogram into subsections (along rotation angle axis).",
     )
     correction_range = param.Tuple(
-        default=(0.9, 1.1), doc="Multiplicative correction factor is capped within given range."
+        default=(0.9, 1.1),
+        doc="Multiplicative correction factor is capped within given range.",
     )
 
     def __call__(self, **params):
@@ -303,7 +321,10 @@ def __call__(self, **params):
         _ = self.instance(**params)
         params = param.ParamOverrides(self, params)
         val = _remove_ring_artifact_Ketcham(
-            params.sinogram, params.kernel_size, params.sub_division, params.correction_range
+            params.sinogram,
+            params.kernel_size,
+            params.sub_division,
+            params.correction_range,
         )
         logger.info("FINISHED Executing Filter: Remove Ring Artifact (Ketcham)")
         return val
@@ -317,7 +338,9 @@ def _remove_ring_artifact_Ketcham(
 ) -> np.ndarray:
     # sanity check
     if sinogram.ndim != 2:
-        raise ValueError("This correction can only be used for a sinogram, i.e. a 2D image.")
+        raise ValueError(
+            "This correction can only be used for a sinogram, i.e. a 2D image."
+        )
     # sub-divide the sinogram into smaller sections
     edges = np.linspace(0, sinogram.shape[0], sub_division + 1).astype(int)
     #
@@ -332,7 +355,9 @@ def _remove_ring_artifact_Ketcham(
         # - skip one window/kernel on both end (mostly air anyway)
         # - correction ratio is capped within specified range
         corr_ratio = np.ones_like(sum_over_angle)
-        corr_ratio[kernel_size:-kernel_size] = (sum_over_angle_smoothed / sum_over_angle)[kernel_size:-kernel_size]
+        corr_ratio[kernel_size:-kernel_size] = (
+            sum_over_angle_smoothed / sum_over_angle
+        )[kernel_size:-kernel_size]
         corr_ratio[corr_ratio < correction_range[0]] = correction_range[0]
         corr_ratio[corr_ratio > correction_range[1]] = correction_range[1]
         #