automatic import of python-pydicom

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+/pydicom-2.3.1.tar.gz
diff --git a/python-pydicom.spec b/python-pydicom.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pydicom
+Version:	2.3.1
+Release:	1
+Summary:	A pure Python package for reading and writing DICOM data
+License:	MIT
+URL:		https://github.com/pydicom/pydicom
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/0d/b6/4bb0f895db75ea0b1e0b925e2b0958ec0eb68b9bc19dc23277e13ba82d96/pydicom-2.3.1.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-numpydoc
+Requires:	python3-matplotlib
+Requires:	python3-pillow
+Requires:	python3-sphinx
+Requires:	python3-sphinx-rtd-theme
+Requires:	python3-sphinx-gallery
+Requires:	python3-sphinxcontrib-napoleon
+Requires:	python3-sphinx-copybutton
+
+%description
+[![unit-tests](https://github.com/pydicom/pydicom/workflows/unit-tests/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Aunit-tests)
+[![type-hints](https://github.com/pydicom/pydicom/workflows/type-hints/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Atype-hints)
+[![doc-build](https://circleci.com/gh/pydicom/pydicom/tree/master.svg?style=shield)](https://circleci.com/gh/pydicom/pydicom/tree/master)
+[![test-coverage](https://codecov.io/gh/pydicom/pydicom/branch/master/graph/badge.svg)](https://codecov.io/gh/pydicom/pydicom)
+[![Python version](https://img.shields.io/pypi/pyversions/pydicom.svg)](https://img.shields.io/pypi/pyversions/pydicom.svg)
+[![PyPI version](https://badge.fury.io/py/pydicom.svg)](https://badge.fury.io/py/pydicom)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6394735.svg)](https://doi.org/10.5281/zenodo.6394735)
+[![Gitter](https://badges.gitter.im/pydicom/Lobby.svg)](https://gitter.im/pydicom/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+
+# *pydicom*
+
+*pydicom* is a pure Python package for working with [DICOM](https://www.dicomstandard.org/) files. It lets you read, modify and write DICOM data in an easy "pythonic" way.
+
+As a pure Python package, *pydicom* can run anywhere Python runs without any other requirements, although if you're working with *Pixel Data* then we recommend you also install [NumPy](http://www.numpy.org).
+
+If you're looking for a Python library for DICOM networking then you might be interested in another of our projects: [pynetdicom](https://github.com/pydicom/pynetdicom).
+
+## Installation
+
+Using [pip](https://pip.pypa.io/en/stable/):
+```
+pip install pydicom
+```
+Using [conda](https://docs.conda.io/en/latest/):
+```
+conda install -c conda-forge pydicom
+```
+
+For more information, including installation instructions for the development version, see the [installation guide](https://pydicom.github.io/pydicom/stable/tutorials/installation.html).
+
+
+## Documentation
+
+The *pydicom* [user guide](https://pydicom.github.io/pydicom/stable/old/pydicom_user_guide.html), [tutorials](https://pydicom.github.io/pydicom/stable/tutorials/index.html), [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) and [API reference](https://pydicom.github.io/pydicom/stable/reference/index.html) documentation is available for both the [current release](https://pydicom.github.io/pydicom/stable) and the [development version](https://pydicom.github.io/pydicom/dev) on GitHub Pages.
+
+## *Pixel Data*
+
+Compressed and uncompressed *Pixel Data* is always available to
+be read, changed and written as [bytes](https://docs.python.org/3/library/stdtypes.html#bytes-objects):
+```python
+>>> from pydicom import dcmread
+>>> from pydicom.data import get_testdata_file
+>>> path = get_testdata_file("CT_small.dcm")
+>>> ds = dcmread(path)
+>>> type(ds.PixelData)
+<class 'bytes'>
+>>> len(ds.PixelData)
+32768
+>>> ds.PixelData[:2]
+b'\xaf\x00'
+
+```
+
+If [NumPy](http://www.numpy.org) is installed, *Pixel Data* can be converted to an [ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) using the [Dataset.pixel_array](https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.dataset.Dataset.html#pydicom.dataset.Dataset.pixel_array) property:
+
+```python
+>>> arr = ds.pixel_array
+>>> arr.shape
+(128, 128)
+>>> arr
+array([[175, 180, 166, ..., 203, 207, 216],
+       [186, 183, 157, ..., 181, 190, 239],
+       [184, 180, 171, ..., 152, 164, 235],
+       ...,
+       [906, 910, 923, ..., 922, 929, 927],
+       [914, 954, 938, ..., 942, 925, 905],
+       [959, 955, 916, ..., 911, 904, 909]], dtype=int16)
+```
+### Compressed *Pixel Data*
+#### JPEG, JPEG-LS and JPEG 2000
+Converting JPEG compressed *Pixel Data* to an ``ndarray`` requires installing one or more additional Python libraries. For information on which libraries are required, see the [pixel data handler documentation](https://pydicom.github.io/pydicom/stable/old/image_data_handlers.html#guide-compressed).
+
+Compressing data into one of the JPEG formats is not currently supported.
+
+#### RLE
+Encoding and decoding RLE *Pixel Data* only requires NumPy, however it can
+be quite slow. You may want to consider [installing one or more additional
+Python libraries](https://pydicom.github.io/pydicom/stable/old/image_data_compression.html) to speed up the process.
+
+## Examples
+More [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) are available in the documentation.
+
+**Change a patient's ID**
+```python
+from pydicom import dcmread
+
+ds = dcmread("/path/to/file.dcm")
+# Edit the (0010,0020) 'Patient ID' element
+ds.PatientID = "12345678"
+ds.save_as("/path/to/file_updated.dcm")
+```
+
+**Display the Pixel Data**
+
+With [NumPy](http://www.numpy.org) and [matplotlib](https://matplotlib.org/)
+```python
+import matplotlib.pyplot as plt
+from pydicom import dcmread
+from pydicom.data import get_testdata_file
+
+# The path to a pydicom test dataset
+path = get_testdata_file("CT_small.dcm")
+ds = dcmread(path)
+# `arr` is a numpy.ndarray
+arr = ds.pixel_array
+
+plt.imshow(arr, cmap="gray")
+plt.show()
+```
+
+## Contributing
+
+To contribute to *pydicom*, read our [contribution guide](https://github.com/pydicom/pydicom/blob/master/CONTRIBUTING.md).
+
+To contribute an example or extension of *pydicom* that doesn't belong with the core software, see our contribution repository:
+[contrib-pydicom](https://www.github.com/pydicom/contrib-pydicom).
+
+
+%package -n python3-pydicom
+Summary:	A pure Python package for reading and writing DICOM data
+Provides:	python-pydicom
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pydicom
+[![unit-tests](https://github.com/pydicom/pydicom/workflows/unit-tests/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Aunit-tests)
+[![type-hints](https://github.com/pydicom/pydicom/workflows/type-hints/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Atype-hints)
+[![doc-build](https://circleci.com/gh/pydicom/pydicom/tree/master.svg?style=shield)](https://circleci.com/gh/pydicom/pydicom/tree/master)
+[![test-coverage](https://codecov.io/gh/pydicom/pydicom/branch/master/graph/badge.svg)](https://codecov.io/gh/pydicom/pydicom)
+[![Python version](https://img.shields.io/pypi/pyversions/pydicom.svg)](https://img.shields.io/pypi/pyversions/pydicom.svg)
+[![PyPI version](https://badge.fury.io/py/pydicom.svg)](https://badge.fury.io/py/pydicom)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6394735.svg)](https://doi.org/10.5281/zenodo.6394735)
+[![Gitter](https://badges.gitter.im/pydicom/Lobby.svg)](https://gitter.im/pydicom/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+
+# *pydicom*
+
+*pydicom* is a pure Python package for working with [DICOM](https://www.dicomstandard.org/) files. It lets you read, modify and write DICOM data in an easy "pythonic" way.
+
+As a pure Python package, *pydicom* can run anywhere Python runs without any other requirements, although if you're working with *Pixel Data* then we recommend you also install [NumPy](http://www.numpy.org).
+
+If you're looking for a Python library for DICOM networking then you might be interested in another of our projects: [pynetdicom](https://github.com/pydicom/pynetdicom).
+
+## Installation
+
+Using [pip](https://pip.pypa.io/en/stable/):
+```
+pip install pydicom
+```
+Using [conda](https://docs.conda.io/en/latest/):
+```
+conda install -c conda-forge pydicom
+```
+
+For more information, including installation instructions for the development version, see the [installation guide](https://pydicom.github.io/pydicom/stable/tutorials/installation.html).
+
+
+## Documentation
+
+The *pydicom* [user guide](https://pydicom.github.io/pydicom/stable/old/pydicom_user_guide.html), [tutorials](https://pydicom.github.io/pydicom/stable/tutorials/index.html), [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) and [API reference](https://pydicom.github.io/pydicom/stable/reference/index.html) documentation is available for both the [current release](https://pydicom.github.io/pydicom/stable) and the [development version](https://pydicom.github.io/pydicom/dev) on GitHub Pages.
+
+## *Pixel Data*
+
+Compressed and uncompressed *Pixel Data* is always available to
+be read, changed and written as [bytes](https://docs.python.org/3/library/stdtypes.html#bytes-objects):
+```python
+>>> from pydicom import dcmread
+>>> from pydicom.data import get_testdata_file
+>>> path = get_testdata_file("CT_small.dcm")
+>>> ds = dcmread(path)
+>>> type(ds.PixelData)
+<class 'bytes'>
+>>> len(ds.PixelData)
+32768
+>>> ds.PixelData[:2]
+b'\xaf\x00'
+
+```
+
+If [NumPy](http://www.numpy.org) is installed, *Pixel Data* can be converted to an [ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) using the [Dataset.pixel_array](https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.dataset.Dataset.html#pydicom.dataset.Dataset.pixel_array) property:
+
+```python
+>>> arr = ds.pixel_array
+>>> arr.shape
+(128, 128)
+>>> arr
+array([[175, 180, 166, ..., 203, 207, 216],
+       [186, 183, 157, ..., 181, 190, 239],
+       [184, 180, 171, ..., 152, 164, 235],
+       ...,
+       [906, 910, 923, ..., 922, 929, 927],
+       [914, 954, 938, ..., 942, 925, 905],
+       [959, 955, 916, ..., 911, 904, 909]], dtype=int16)
+```
+### Compressed *Pixel Data*
+#### JPEG, JPEG-LS and JPEG 2000
+Converting JPEG compressed *Pixel Data* to an ``ndarray`` requires installing one or more additional Python libraries. For information on which libraries are required, see the [pixel data handler documentation](https://pydicom.github.io/pydicom/stable/old/image_data_handlers.html#guide-compressed).
+
+Compressing data into one of the JPEG formats is not currently supported.
+
+#### RLE
+Encoding and decoding RLE *Pixel Data* only requires NumPy, however it can
+be quite slow. You may want to consider [installing one or more additional
+Python libraries](https://pydicom.github.io/pydicom/stable/old/image_data_compression.html) to speed up the process.
+
+## Examples
+More [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) are available in the documentation.
+
+**Change a patient's ID**
+```python
+from pydicom import dcmread
+
+ds = dcmread("/path/to/file.dcm")
+# Edit the (0010,0020) 'Patient ID' element
+ds.PatientID = "12345678"
+ds.save_as("/path/to/file_updated.dcm")
+```
+
+**Display the Pixel Data**
+
+With [NumPy](http://www.numpy.org) and [matplotlib](https://matplotlib.org/)
+```python
+import matplotlib.pyplot as plt
+from pydicom import dcmread
+from pydicom.data import get_testdata_file
+
+# The path to a pydicom test dataset
+path = get_testdata_file("CT_small.dcm")
+ds = dcmread(path)
+# `arr` is a numpy.ndarray
+arr = ds.pixel_array
+
+plt.imshow(arr, cmap="gray")
+plt.show()
+```
+
+## Contributing
+
+To contribute to *pydicom*, read our [contribution guide](https://github.com/pydicom/pydicom/blob/master/CONTRIBUTING.md).
+
+To contribute an example or extension of *pydicom* that doesn't belong with the core software, see our contribution repository:
+[contrib-pydicom](https://www.github.com/pydicom/contrib-pydicom).
+
+
+%package help
+Summary:	Development documents and examples for pydicom
+Provides:	python3-pydicom-doc
+%description help
+[![unit-tests](https://github.com/pydicom/pydicom/workflows/unit-tests/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Aunit-tests)
+[![type-hints](https://github.com/pydicom/pydicom/workflows/type-hints/badge.svg)](https://github.com/pydicom/pydicom/actions?query=workflow%3Atype-hints)
+[![doc-build](https://circleci.com/gh/pydicom/pydicom/tree/master.svg?style=shield)](https://circleci.com/gh/pydicom/pydicom/tree/master)
+[![test-coverage](https://codecov.io/gh/pydicom/pydicom/branch/master/graph/badge.svg)](https://codecov.io/gh/pydicom/pydicom)
+[![Python version](https://img.shields.io/pypi/pyversions/pydicom.svg)](https://img.shields.io/pypi/pyversions/pydicom.svg)
+[![PyPI version](https://badge.fury.io/py/pydicom.svg)](https://badge.fury.io/py/pydicom)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6394735.svg)](https://doi.org/10.5281/zenodo.6394735)
+[![Gitter](https://badges.gitter.im/pydicom/Lobby.svg)](https://gitter.im/pydicom/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+
+# *pydicom*
+
+*pydicom* is a pure Python package for working with [DICOM](https://www.dicomstandard.org/) files. It lets you read, modify and write DICOM data in an easy "pythonic" way.
+
+As a pure Python package, *pydicom* can run anywhere Python runs without any other requirements, although if you're working with *Pixel Data* then we recommend you also install [NumPy](http://www.numpy.org).
+
+If you're looking for a Python library for DICOM networking then you might be interested in another of our projects: [pynetdicom](https://github.com/pydicom/pynetdicom).
+
+## Installation
+
+Using [pip](https://pip.pypa.io/en/stable/):
+```
+pip install pydicom
+```
+Using [conda](https://docs.conda.io/en/latest/):
+```
+conda install -c conda-forge pydicom
+```
+
+For more information, including installation instructions for the development version, see the [installation guide](https://pydicom.github.io/pydicom/stable/tutorials/installation.html).
+
+
+## Documentation
+
+The *pydicom* [user guide](https://pydicom.github.io/pydicom/stable/old/pydicom_user_guide.html), [tutorials](https://pydicom.github.io/pydicom/stable/tutorials/index.html), [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) and [API reference](https://pydicom.github.io/pydicom/stable/reference/index.html) documentation is available for both the [current release](https://pydicom.github.io/pydicom/stable) and the [development version](https://pydicom.github.io/pydicom/dev) on GitHub Pages.
+
+## *Pixel Data*
+
+Compressed and uncompressed *Pixel Data* is always available to
+be read, changed and written as [bytes](https://docs.python.org/3/library/stdtypes.html#bytes-objects):
+```python
+>>> from pydicom import dcmread
+>>> from pydicom.data import get_testdata_file
+>>> path = get_testdata_file("CT_small.dcm")
+>>> ds = dcmread(path)
+>>> type(ds.PixelData)
+<class 'bytes'>
+>>> len(ds.PixelData)
+32768
+>>> ds.PixelData[:2]
+b'\xaf\x00'
+
+```
+
+If [NumPy](http://www.numpy.org) is installed, *Pixel Data* can be converted to an [ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) using the [Dataset.pixel_array](https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.dataset.Dataset.html#pydicom.dataset.Dataset.pixel_array) property:
+
+```python
+>>> arr = ds.pixel_array
+>>> arr.shape
+(128, 128)
+>>> arr
+array([[175, 180, 166, ..., 203, 207, 216],
+       [186, 183, 157, ..., 181, 190, 239],
+       [184, 180, 171, ..., 152, 164, 235],
+       ...,
+       [906, 910, 923, ..., 922, 929, 927],
+       [914, 954, 938, ..., 942, 925, 905],
+       [959, 955, 916, ..., 911, 904, 909]], dtype=int16)
+```
+### Compressed *Pixel Data*
+#### JPEG, JPEG-LS and JPEG 2000
+Converting JPEG compressed *Pixel Data* to an ``ndarray`` requires installing one or more additional Python libraries. For information on which libraries are required, see the [pixel data handler documentation](https://pydicom.github.io/pydicom/stable/old/image_data_handlers.html#guide-compressed).
+
+Compressing data into one of the JPEG formats is not currently supported.
+
+#### RLE
+Encoding and decoding RLE *Pixel Data* only requires NumPy, however it can
+be quite slow. You may want to consider [installing one or more additional
+Python libraries](https://pydicom.github.io/pydicom/stable/old/image_data_compression.html) to speed up the process.
+
+## Examples
+More [examples](https://pydicom.github.io/pydicom/stable/auto_examples/index.html) are available in the documentation.
+
+**Change a patient's ID**
+```python
+from pydicom import dcmread
+
+ds = dcmread("/path/to/file.dcm")
+# Edit the (0010,0020) 'Patient ID' element
+ds.PatientID = "12345678"
+ds.save_as("/path/to/file_updated.dcm")
+```
+
+**Display the Pixel Data**
+
+With [NumPy](http://www.numpy.org) and [matplotlib](https://matplotlib.org/)
+```python
+import matplotlib.pyplot as plt
+from pydicom import dcmread
+from pydicom.data import get_testdata_file
+
+# The path to a pydicom test dataset
+path = get_testdata_file("CT_small.dcm")
+ds = dcmread(path)
+# `arr` is a numpy.ndarray
+arr = ds.pixel_array
+
+plt.imshow(arr, cmap="gray")
+plt.show()
+```
+
+## Contributing
+
+To contribute to *pydicom*, read our [contribution guide](https://github.com/pydicom/pydicom/blob/master/CONTRIBUTING.md).
+
+To contribute an example or extension of *pydicom* that doesn't belong with the core software, see our contribution repository:
+[contrib-pydicom](https://www.github.com/pydicom/contrib-pydicom).
+
+
+%prep
+%autosetup -n pydicom-2.3.1
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-pydicom -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu Mar 09 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..bcba9e4
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+33d62d148b2baa678fcc790571cfced6  pydicom-2.3.1.tar.gz