move function of data/dicom_util to file/dicom

mu_map/data/dicom_util.py

-from datetime import datetime
-from enum import Enum
-
-import pydicom
-
-
-class DICOMTime(Enum):
-    Study = 1
-    Series = 2
-    Acquisition = 3
-    Content = 4
-
-    def date_field(self):
-        return f"{self.name}Date"
-
-    def time_field(self):
-        return f"{self.name}Time"
-
-    def to_datetime(self, dicom: pydicom.dataset.FileDataset) -> datetime:
-        _date = dicom[self.date_field()].value
-        _time = dicom[self.time_field()].value
-        return datetime(
-            year=int(_date[0:4]),
-            month=int(_date[4:6]),
-            day=int(_date[6:8]),
-            hour=int(_time[0:2]),
-            minute=int(_time[2:4]),
-            second=int(_time[4:6]),
-            # microsecond=int(_time.split(".")[1]),
-        )
-        
-
-def parse_age(patient_age: str) -> int:
-    """
-    Parse an age string as defined in the DICOM standard into an integer representing the age in years.
-
-    :param patient_age: age string as defined in the DICOM standard
-    :return: the age in years as a number
-    """
-    assert (
-        type(patient_age) == str
-    ), f"patient age needs to be a string and not {type(patient_age)}"
-    assert (
-        len(patient_age) == 4
-    ), f"patient age [{patient_age}] has to be four characters long"
-    _num, _format = patient_age[:3], patient_age[3]
-    assert (
-        _format == "Y"
-    ), f"currently, only patient ages in years [Y] is supported, not [{_format}]"
-    return int(_num)

mu_map/data/prepare.py

@@ -8,7 +8,7 @@ import numpy as np
 import pandas as pd
 import pydicom
 
-from mu_map.data.dicom_util import DICOMTime, parse_age
+from mu_map.file.dicom import DICOMTime, parse_age
 from mu_map.logging import add_logging_args, get_logger_by_args
 
 

mu_map/file/dicom.py

+from datetime import datetime
+from enum import Enum
 import random
 from typing import Tuple
 
@@ -29,6 +31,69 @@ Default extension of dicom files.
 EXTENSION_DICOM = ".dcm"
 
 
+class DICOMTime(Enum):
+    """
+    Class for parsing dates and times defined in a DICOM header
+    into a python datetime type. It maps the four datetime fields
+    [Study, Series, Acquisition, Content] of the DICOM header into
+    an enumeration type.
+
+    Usage: DICOMTime.Series.to_datetime(dcm)
+    """
+
+    Study = 1
+    Series = 2
+    Acquisition = 3
+    Content = 4
+
+    def date_field(self) -> str:
+        """
+        Get the name of the date field according to this DICOMTime type.
+        """
+        return f"{self.name}Date"
+
+    def time_field(self) -> str:
+        """
+        Get the name of the time field according to this DICOMTime type.
+        """
+        return f"{self.name}Time"
+
+    def to_datetime(self, dicom: dcm_type) -> datetime:
+        """
+        Get the datetime according to this DICOMTime type.
+        """
+        _date = dicom[self.date_field()].value
+        _time = dicom[self.time_field()].value
+        return datetime(
+            year=int(_date[0:4]),
+            month=int(_date[4:6]),
+            day=int(_date[6:8]),
+            hour=int(_time[0:2]),
+            minute=int(_time[2:4]),
+            second=int(_time[4:6]),
+        )
+
+
+def parse_age(patient_age: str) -> int:
+    """
+    Parse an age string as defined in the DICOM standard into an integer representing the age in years.
+
+    :param patient_age: age string as defined in the DICOM standard
+    :return: the age in years as a number
+    """
+    assert (
+        type(patient_age) == str
+    ), f"patient age needs to be a string and not {type(patient_age)}"
+    assert (
+        len(patient_age) == 4
+    ), f"patient age [{patient_age}] has to be four characters long"
+    _num, _format = patient_age[:3], patient_age[3]
+    assert (
+        _format == "Y"
+    ), f"currently, only patient ages in years [Y] is supported, not [{_format}]"
+    return int(_num)
+
+
 def load_dcm(filename: str) -> Tuple[pydicom.dataset.FileDataset, np.ndarray]:
     """
     Load a DICOM image, the data as a numpy array and apply normalization of the Siemens SPECT/CT
@@ -69,7 +134,7 @@ def scale_image(image: np.ndarray, initial_scale=10000000) -> Tuple[np.ndarray,
     is smaller than the maximum uint16 number
     :return: the image scaled and converted to uint16 as well as the used scaling factor
     """
-    if image.min()  < 0.0:
+    if image.min() < 0.0:
         raise ValueError("Cannot scale images with negative values!")
 
     scale = initial_scale
@@ -121,15 +186,25 @@ def change_uid(dcm: pydicom.dataset.FileDataset) -> pydicom.dataset.FileDataset:
     :param dcm: the DICOM file to be udpated
     :return: the DICOM file with updated UIDs
     """
-    dcm.SeriesInstanceUID = UID_PREFIX + str(random.randint(10000000000000, 99999999999999))
-    dcm.SOPInstanceUID = UID_PREFIX + str(random.randint(10000000000000, 99999999999999))
+    dcm.SeriesInstanceUID = UID_PREFIX + str(
+        random.randint(10000000000000, 99999999999999)
+    )
+    dcm.SOPInstanceUID = UID_PREFIX + str(
+        random.randint(10000000000000, 99999999999999)
+    )
     return dcm
 
+
 if __name__ == "__main__":
     import argparse
 
-    parser = argparse.ArgumentParser(description="Dump the header of a DICOM image", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-    parser.add_argument("file", type=str, help="the DICOM file of which the header is dumped")
+    parser = argparse.ArgumentParser(
+        description="Dump the header of a DICOM image",
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument(
+        "file", type=str, help="the DICOM file of which the header is dumped"
+    )
     args = parser.parse_args()
 
     dcm = pydicom.dcmread(args.file)