black

tomoscan/esrf/scan/framereducer/edfframereducer.py

@@ -47,7 +47,6 @@ _logger = logging.getLogger(__name__)
 
 
 class EDFFrameReducer(FrameReducerBase):
-
     RAW_FLAT_RE = "ref*.*[0-9]{3,4}_[0-9]{3,4}"
     """regular expression to discover flat files"""
 
@@ -364,7 +363,6 @@ class EDFFrameReducer(FrameReducerBase):
         return res, infos
 
     def preprocess(self):
-
         # start setup function
         if self.reduced_method is ReduceMethod.NONE:
             return False

tomoscan/esrf/scan/framereducer/test/test_edfframereducer.py

@@ -55,7 +55,6 @@ class MockEDFWithRawRef(_MockEDF):
         electrical_current: Optional[numpy.array] = None,
         count_time: Optional[numpy.array] = None,
     ):
-
         self.flat_n = len(flats[list(flats.keys())[0]]) if len(flats) > 0 else 0
         self.dark_n = len(flats[list(darks.keys())[0]]) if len(darks) > 0 else 0
         self.flats = flats

tomoscan/esrf/scan/mock.py

@@ -394,7 +394,6 @@ class MockHDF5(ScanMock):
         y_pos=None,
         z_pos=None,
     ):
-
         with h5py.File(self.scan_master_file, "a") as h5_file:
             entry_one = h5_file.require_group(self.scan_entry)
             instrument_grp = entry_one.require_group("instrument")

tomoscan/esrf/scan/test/test_hdf5scan.py

@@ -558,7 +558,6 @@ def test_HDF5TomoScan_nxversion():
         distance=1.0,
         energy=1.0,
     ) as scan:
-
         hdf5scan = HDF5TomoScan(scan.master_file)
         # The default behavior is to take NX 1.1 if not present in file metadata
         # This is not future-proof, perhaps do a _NEXUS_PATHS_LATEST class ?

tomoscan/esrf/scan/utils.py

@@ -333,7 +333,7 @@ def get_datasets_linked_to_vds(url: DataUrl):
         to_treat = list(virtual_dataset_to_treat)
         virtual_dataset_to_treat.clear()
 
-        for (file_path, dataset_path, dataset_slice) in to_treat:
+        for file_path, dataset_path, dataset_slice in to_treat:
             if (file_path, dataset_path, dataset_slice) in already_checked:
                 continue
             if os.path.exists(file_path):

tomoscan/identifier.py

@@ -29,7 +29,6 @@ __date__ = "10/01/2022"
 
 
 class BaseIdentifier:
-
     TOMO_TYPE = None
 
     def __init__(self, object):

tomoscan/nexus/paths/nxmonitor.py

 class NEXUS_MONITOR_PATH:
-
     DATA_PATH = "data"
 
 

tomoscan/nexus/paths/nxtomo.py

@@ -300,7 +300,6 @@ class NXtomo_PATH:
 
 
 class NXtomo_PATH_v_1_0(NXtomo_PATH):
-
     VERSION = 1.0
 
     _NX_DETECTOR_PATHS = nxdetector.NEXUS_DETECTOR_PATH_V_1_0
@@ -314,7 +313,6 @@ nx_tomo_path_v_1_0 = NXtomo_PATH_v_1_0()
 
 
 class NXtomo_PATH_v_1_1(NXtomo_PATH_v_1_0):
-
     VERSION = 1.1
 
     _NX_DETECTOR_PATHS = nxdetector.NEXUS_DETECTOR_PATH_V_1_1
@@ -369,7 +367,6 @@ nx_tomo_path_v_1_1 = NXtomo_PATH_v_1_1()
 
 
 class NXtomo_PATH_v_1_2(NXtomo_PATH_v_1_1):
-
     VERSION = 1.2
 
     _NX_DETECTOR_PATHS = nxdetector.NEXUS_DETECTOR_PATH_V_1_2

tomoscan/nexus/paths/test/test_backward_compatibility.py

@@ -115,7 +115,6 @@ class _NEXUS_PATHS_V_1_0(_NEXUS_PATHS):
 
 
 class _NEXUS_PATHS_V_1_1(_NEXUS_PATHS_V_1_0):
-
     ENERGY_PATH = "instrument/beam/incident_energy"
 
     SOURCE_NAME = "instrument/source/name"

tomoscan/scanbase.py

@@ -1419,7 +1419,7 @@ class TomoScanBase(TomoObject):
                     data_path = data_path[:-1]
                 return data_path, index_zfill4_pattern
 
-            for (frame_file_path, frame_index) in frames_path_and_index:
+            for frame_file_path, frame_index in frames_path_and_index:
                 if scheme == "fabio":
                     if not os.path.exists(frame_file_path):
                         continue
@@ -1478,7 +1478,7 @@ class TomoScanBase(TomoObject):
                                 dataset_or_group, h5py.Group
                             ), f"expect a group not {type(dataset_or_group)}"
                             # browse childrens
-                            for (name, item) in dataset_or_group.items():
+                            for name, item in dataset_or_group.items():
                                 if isinstance(item, h5py.Dataset):
                                     if name.isnumeric():
                                         if index_zfill4_pattern and not len(name) == 4: