Merge pull request #27 from jond01/master

Maintenance - python 3.6+, pydicom 1.0+

Author: johndgiese

.travis.yml

@@ -1,10 +1,10 @@
 sudo: false
 language: python
 python:
-    - "2.7"
-    - "3.5"
     - "3.6"
     - "3.7"
+    - "3.8"
+    - "3.9"
 install: pip install tox-travis
 script: tox
 notifications:

LICENSE.txt

@@ -1,4 +1,4 @@
-Copyright (c) 2017 Innolitics, LLC.
+Copyright (c) 2017-2021 Innolitics, LLC.
 
 Permission is hereby granted, free of charge, to any person obtaining a copy of
 this software and associated documentation files (the "Software"), to deal in

dicom_numpy/__init__.py

@@ -1,8 +1,11 @@
 from .combine_slices import combine_slices, sort_by_slice_position
 from .exceptions import DicomImportException
 
+__version__ = '0.5.0'
+
 __all__ = [
     'combine_slices',
     'sort_by_slice_position',
     'DicomImportException',
+    '__version__'
 ]

dicom_numpy/combine_slices.py

@@ -1,8 +1,8 @@
 import logging
+from math import isclose
 
 import numpy as np
 
-from .utils import isclose
 from .exceptions import DicomImportException
 
 
@@ -180,19 +180,19 @@ def _validate_image_orientation(image_orientation):
     row_cosine, column_cosine, slice_cosine = _extract_cosines(image_orientation)
 
     if not _almost_zero(np.dot(row_cosine, column_cosine), 1e-4):
-        raise DicomImportException("Non-orthogonal direction cosines: {}, {}".format(row_cosine, column_cosine))
+        raise DicomImportException(f"Non-orthogonal direction cosines: {row_cosine}, {column_cosine}")
     elif not _almost_zero(np.dot(row_cosine, column_cosine), 1e-8):
-        logger.warning("Direction cosines aren't quite orthogonal: {}, {}".format(row_cosine, column_cosine))
+        logger.warning(f"Direction cosines aren't quite orthogonal: {row_cosine}, {column_cosine}")
 
     if not _almost_one(np.linalg.norm(row_cosine), 1e-4):
-        raise DicomImportException("The row direction cosine's magnitude is not 1: {}".format(row_cosine))
+        raise DicomImportException(f"The row direction cosine's magnitude is not 1: {row_cosine}")
     elif not _almost_one(np.linalg.norm(row_cosine), 1e-8):
-        logger.warning("The row direction cosine's magnitude is not quite 1: {}".format(row_cosine))
+        logger.warning(f"The row direction cosine's magnitude is not quite 1: {row_cosine}")
 
     if not _almost_one(np.linalg.norm(column_cosine), 1e-4):
-        raise DicomImportException("The column direction cosine's magnitude is not 1: {}".format(column_cosine))
+        raise DicomImportException(f"The column direction cosine's magnitude is not 1: {column_cosine}")
     elif not _almost_one(np.linalg.norm(column_cosine), 1e-8):
-        logger.warning("The column direction cosine's magnitude is not quite 1: {}".format(column_cosine))
+        logger.warning(f"The column direction cosine's magnitude is not quite 1: {column_cosine}")
 
 
 def _almost_zero(value, abs_tol):
@@ -215,17 +215,18 @@ def _slice_attribute_equal(slice_datasets, property_name):
     for dataset in slice_datasets[1:]:
         value = getattr(dataset, property_name, None)
         if value != initial_value:
-            msg = 'All slices must have the same value for "{}": {} != {}'
-            raise DicomImportException(msg.format(property_name, value, initial_value))
+            msg = f'All slices must have the same value for "{property_name}": {value} != {initial_value}'
+            raise DicomImportException(msg)
 
 
 def _slice_ndarray_attribute_almost_equal(slice_datasets, property_name, abs_tol):
     initial_value = getattr(slice_datasets[0], property_name, None)
     for dataset in slice_datasets[1:]:
         value = getattr(dataset, property_name, None)
         if not np.allclose(value, initial_value, atol=abs_tol):
-            msg = 'All slices must have the same value for "{}" within "{}": {} != {}'
-            raise DicomImportException(msg.format(property_name, abs_tol, value, initial_value))
+            msg = (f'All slices must have the same value for "{property_name}" within "{abs_tol}": {value} != '
+                   f'{initial_value}')
+            raise DicomImportException(msg)
 
 
 def _slice_positions(slice_datasets):
@@ -239,8 +240,8 @@ def _check_for_missing_slices(slice_positions):
         slice_positions_diffs = np.diff(sorted(slice_positions))
         if not np.allclose(slice_positions_diffs, slice_positions_diffs[0], atol=0, rtol=1e-5):
             # TODO: figure out how we should handle non-even slice spacing
-            msg = "The slice spacing is non-uniform. Slice spacings:\n{}"
-            logger.warning(msg.format(slice_positions_diffs))
+            msg = f"The slice spacing is non-uniform. Slice spacings:\n{slice_positions_diffs}"
+            logger.warning(msg)
 
         if not np.allclose(slice_positions_diffs, slice_positions_diffs[0], atol=0, rtol=1e-1):
             raise DicomImportException('It appears there are missing slices')

dicom_numpy/utils.py

@@ -2,10 +2,7 @@
 import logging
 import tempfile
 
-try:
-    import pydicom as dicom
-except ImportError:
-    import dicom
+import pydicom
 
 from .exceptions import DicomImportException
 from .combine_slices import combine_slices
@@ -15,10 +12,10 @@
 
 
 def combined_series_from_zip(zip_filename):
-    logger.info('Extracting voxel data from "{}"'.format(zip_filename))
+    logger.info(f'Extracting voxel data from "{zip_filename}"')
 
     if not zipfile.is_zipfile(zip_filename):
-        raise DicomImportException('Invalid zipfile {}'.format(zip_filename))
+        raise DicomImportException(f'Invalid zipfile {zip_filename}')
 
     with zipfile.ZipFile(zip_filename, 'r') as zip_file:
         datasets = dicom_datasets_from_zip(zip_file)
@@ -36,21 +33,21 @@ def dicom_datasets_from_zip(zip_file):
         entry_pseudo_file = zip_file.open(entry)
 
         # the pseudo file does not support `seek`, which is required by
-        # dicom's lazy loading mechanism; use temporary files to get around this;
+        # pydicom's lazy loading mechanism; use temporary files to get around this;
         # relies on the temporary files not being removed until the temp
         # file is garbage collected, which should be the case because the
-        # dicom datasets should retain a reference to the temp file
+        # pydicom datasets should retain a reference to the temp file
         temp_file = tempfile.TemporaryFile()
         temp_file.write(entry_pseudo_file.read())
         temp_file.flush()
         temp_file.seek(0)
 
         try:
-            dataset = dicom.read_file(temp_file)
+            dataset = pydicom.read_file(temp_file)
             datasets.append(dataset)
-        except dicom.errors.InvalidDicomError as e:
-            msg = 'Skipping invalid DICOM file "{}": {}'
-            logger.info(msg.format(entry, e))
+        except pydicom.errors.InvalidDicomError as e:
+            msg = f'Skipping invalid DICOM file "{entry}": {e}'
+            logger.info(msg)
 
     if len(datasets) == 0:
         raise DicomImportException('Zipfile does not contain any valid DICOM files')

dicom_numpy/zip_archive.py

@@ -20,10 +20,7 @@
 import os
 import sys
 
-try:
-    from unittest.mock import MagicMock
-except ImportError:
-    from mock import Mock as MagicMock
+from unittest.mock import MagicMock
 
 sys.path.insert(0, os.path.abspath('../..'))
 
@@ -34,7 +31,7 @@ def __getattr__(cls, name):
         return MagicMock()
 
 
-MOCK_MODULES = ['numpy', 'dicom']
+MOCK_MODULES = ['numpy', 'pydicom']
 sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
 
 

docs/requirements.txt

@@ -4,7 +4,7 @@ DICOM-Numpy
 
 This python module provides a set of utilities for extracting data contained in
 DICOM files into Numpy ndarrays.  It is a higher-level library that builds on the excellent lower-level `pydicom
-<http://pydicom.readthedocs.io/en/stable/>`_ library.
+<https://pydicom.github.io/pydicom/>`_ library.
 
 The library is quite small at the moment, however, if you have a DICOM-related
 utility function that you think would be appropriate to include, create a
@@ -13,9 +13,9 @@ Github Issue!
 Dependencies
 ============
 
-- Python 2.7 or Python 3.5+
+- Python 3.6+
 - Numpy
-- PyDicom
+- PyDicom 1.0+
 
 
 Installation
@@ -41,18 +41,18 @@ single 3D image into a single scan.
 
 The function that performs this task is `combine_slices`.  Since this library
 builds on pydicom, `combine_slices` takes an list of `pydicom
-datasets <http://pydicom.readthedocs.io/en/stable/pydicom_user_guide.html#dataset>`_.
+datasets <https://pydicom.github.io/pydicom/stable/old/base_element.html#dataset>`_.
 
 Example
 -------
 
 .. code:: python
 
-    import dicom
+    import pydicom
     import dicom_numpy
 
     def extract_voxel_data(list_of_dicom_files):
-        datasets = [dicom.read_file(f) for f in list_of_dicom_files]
+        datasets = [pydicom.dcmread(f) for f in list_of_dicom_files]
         try:
             voxel_ndarray, ijk_to_xyz = dicom_numpy.combine_slices(datasets)
         except dicom_numpy.DicomImportException as e:

docs/source/conf.py

@@ -3,17 +3,18 @@
 """
 
 from setuptools import setup, find_packages
-from codecs import open
 from os import path
 
+from dicom_numpy import __version__
+
 here = path.abspath(path.dirname(__file__))
 
 with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
     long_description = f.read()
 
 setup(
     name='dicom_numpy',
-    version='0.5.0',
+    version=__version__,
     description='Extract image data into a 3D numpy array from a set of DICOM files.',
     long_description=long_description,
     url='https://github.com/innolitics/dicom-numpy',
@@ -30,29 +31,26 @@
 
         'License :: OSI Approved :: MIT License',
 
-        'Programming Language :: Python :: 2',
-        'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
+        'Programming Language :: Python :: 3.9'
     ],
 
     keywords='dicom numpy',
 
     packages=find_packages(exclude=['contrib', 'docs', 'tests']),
 
     install_requires=[
-        'pydicom',
+        'pydicom >= 1.0',
         'numpy',
     ],
 
-    extras_require={
-        'dev': ['check-manifest', 'sphinx', 'sphinx-autobuild', 'mock'],
-        'test': ['coverage', 'pytest'],
-    },
+    python_requires='>= 3.6',
 
-    package_data={},
-    data_files=[],
-    entry_points={},
+    extras_require={
+        'dev': ['check-manifest', 'sphinx', 'sphinx-autobuild'],
+        'test': ['coverage', 'pytest']
+    }
 )