automatic import of python-compressed-segmentationopeneuler20.03

3 files changed, 406 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..c5bf165 100644
--- a/.gitignore
+++ b/.gitignore
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+/compressed_segmentation-2.2.0.tar.gz
diff --git a/python-compressed-segmentation.spec b/python-compressed-segmentation.spec
new file mode 100644
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--- /dev/null
+++ b/python-compressed-segmentation.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-compressed-segmentation
+Version:	2.2.0
+Release:	1
+Summary:	Neuroglancer compressed_segmentation codec.
+License:	LICENSE.txt
+URL:		https://github.com/janelia-flyem/compressedseg
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/bb/2d/f68952c7a3c808e44654e3402f5fa6d2c8c58b8652dc34ed9fbd1de0636a/compressed_segmentation-2.2.0.tar.gz
+
+Requires:	python3-click
+Requires:	python3-numpy
+Requires:	python3-pytest
+
+%description
+[![PyPI version](https://badge.fury.io/py/compressed-segmentation.svg)](https://badge.fury.io/py/compressed-segmentation) 
+
+# Compress Seg [![Picture](https://raw.github.com/janelia-flyem/janelia-flyem.github.com/master/images/HHMI_Janelia_Color_Alternate_180x40.png)](http://www.janelia.org)
+## Library for compressing and decompressing image segmentation (adapted from [neuroglancer](https://github.com/google/neuroglancer))
+
+```python
+import compressed_segmentation as cseg
+
+sx, sy, sz = (128,128,128)
+dtype = np.uint64
+order = 'C'
+
+labels = np.arange(0, sx*sy*sz, dtype=dtype).reshape((sx,sy,sz), order=order)
+compressed = cseg.compress(labels, order=order)
+recovered = cseg.decompress(
+    compressed, (sx,sy,sz) dtype=dtype, order=order
+)
+
+arr = CompressedSegmentationArray(
+    compressed, shape=(sx,sy,sz), dtype=dtype
+)
+label = arr[54,32,103] # random access to single voxels w/o decompressing
+uniq_labels = arr.labels() # get all distinct values w/o decompressing
+binary2 = arr.remap({ 1: 2 }, preserve_missing_labels=False) # remap labels in segmentation w/o decompressing
+recovered = arr.numpy() # decompress to a numpy array, same as decompress
+124213 in arr # test if a value is in the array
+```
+
+```bash
+cseg compress connectomics.npy
+cseg decompress connectomics.npy.cseg --volume-size 512,512,512 --bytes 4
+````
+
+
+NOTE: This repository is the PyPI distribution repo but is based on work done by Jeremy Maitin-Shepard (Google), Stephen Plaza (Janelia Research Campus), and William Silversmith (Princeton) here: https://github.com/janelia-flyem/compressedseg
+
+This library contains routined to decompress and compress segmentation and to manipulate compressed segmentation data defined by the [neuroglancer project](https://github.com/google/neuroglancer/blob/master/src/neuroglancer/sliceview/compressed_segmentation/README.md). compressed_segmentation essentially renumbers large bit width labels to smaller ones in chunks. This provides for large reductions in memory usage and higher compression.
+
+Note that limitations in the compressed_segmentation format restrict the size of the chunk that can be compressed. As this limitation is data dependent, for example a random array with 1024 labels passes testing at 256x256x128, but 256x256x256 often does not.
+
+
+### Features
+
+* Compression and decompression
+* Random access to voxels without decompression
+* Read out unique values without decompression
+* Remap labels without decompression
+* Command line interface for numpy files
+* (TBD) Interface to relabel and manipulate segmentation from the compressed data
+* C++, Python, and Go interface (see original repo for Golang)
+
+### C++ Compilation
+
+Compiling as a shared library. Feel free to subsititute e.g. clang for the C++ compiler.
+
+```bash
+g++ -std=c++11 -O3 -fPIC -shared -I./include src/compress_segmentation.cc src/decompress_segmentation.cc -o compress_segmentation.so
+```
+
+### Python Installation
+
+#### `pip` Binary Installation  
+
+```bash
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+If there are pre-built binaries available for your architecture this should just work. 
+
+#### `pip` Source Installation 
+
+If you need to build from source, you will need to have a C++ compiler installed:
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install numpy
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+#### Direct Installation  
+
+_Requires a C++ compiler such as g++ or clang._
+
+Works with both Python 2 and 3. Encodes from / decodes to 3D or 4D numpy ndarrays.  
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install -r requirements.txt
+$ python setup.py install
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+### License
+
+Please see the licenses in this repo.
+
+
+
+
+
+%package -n python3-compressed-segmentation
+Summary:	Neuroglancer compressed_segmentation codec.
+Provides:	python-compressed-segmentation
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-compressed-segmentation
+[![PyPI version](https://badge.fury.io/py/compressed-segmentation.svg)](https://badge.fury.io/py/compressed-segmentation) 
+
+# Compress Seg [![Picture](https://raw.github.com/janelia-flyem/janelia-flyem.github.com/master/images/HHMI_Janelia_Color_Alternate_180x40.png)](http://www.janelia.org)
+## Library for compressing and decompressing image segmentation (adapted from [neuroglancer](https://github.com/google/neuroglancer))
+
+```python
+import compressed_segmentation as cseg
+
+sx, sy, sz = (128,128,128)
+dtype = np.uint64
+order = 'C'
+
+labels = np.arange(0, sx*sy*sz, dtype=dtype).reshape((sx,sy,sz), order=order)
+compressed = cseg.compress(labels, order=order)
+recovered = cseg.decompress(
+    compressed, (sx,sy,sz) dtype=dtype, order=order
+)
+
+arr = CompressedSegmentationArray(
+    compressed, shape=(sx,sy,sz), dtype=dtype
+)
+label = arr[54,32,103] # random access to single voxels w/o decompressing
+uniq_labels = arr.labels() # get all distinct values w/o decompressing
+binary2 = arr.remap({ 1: 2 }, preserve_missing_labels=False) # remap labels in segmentation w/o decompressing
+recovered = arr.numpy() # decompress to a numpy array, same as decompress
+124213 in arr # test if a value is in the array
+```
+
+```bash
+cseg compress connectomics.npy
+cseg decompress connectomics.npy.cseg --volume-size 512,512,512 --bytes 4
+````
+
+
+NOTE: This repository is the PyPI distribution repo but is based on work done by Jeremy Maitin-Shepard (Google), Stephen Plaza (Janelia Research Campus), and William Silversmith (Princeton) here: https://github.com/janelia-flyem/compressedseg
+
+This library contains routined to decompress and compress segmentation and to manipulate compressed segmentation data defined by the [neuroglancer project](https://github.com/google/neuroglancer/blob/master/src/neuroglancer/sliceview/compressed_segmentation/README.md). compressed_segmentation essentially renumbers large bit width labels to smaller ones in chunks. This provides for large reductions in memory usage and higher compression.
+
+Note that limitations in the compressed_segmentation format restrict the size of the chunk that can be compressed. As this limitation is data dependent, for example a random array with 1024 labels passes testing at 256x256x128, but 256x256x256 often does not.
+
+
+### Features
+
+* Compression and decompression
+* Random access to voxels without decompression
+* Read out unique values without decompression
+* Remap labels without decompression
+* Command line interface for numpy files
+* (TBD) Interface to relabel and manipulate segmentation from the compressed data
+* C++, Python, and Go interface (see original repo for Golang)
+
+### C++ Compilation
+
+Compiling as a shared library. Feel free to subsititute e.g. clang for the C++ compiler.
+
+```bash
+g++ -std=c++11 -O3 -fPIC -shared -I./include src/compress_segmentation.cc src/decompress_segmentation.cc -o compress_segmentation.so
+```
+
+### Python Installation
+
+#### `pip` Binary Installation  
+
+```bash
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+If there are pre-built binaries available for your architecture this should just work. 
+
+#### `pip` Source Installation 
+
+If you need to build from source, you will need to have a C++ compiler installed:
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install numpy
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+#### Direct Installation  
+
+_Requires a C++ compiler such as g++ or clang._
+
+Works with both Python 2 and 3. Encodes from / decodes to 3D or 4D numpy ndarrays.  
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install -r requirements.txt
+$ python setup.py install
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+### License
+
+Please see the licenses in this repo.
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for compressed-segmentation
+Provides:	python3-compressed-segmentation-doc
+%description help
+[![PyPI version](https://badge.fury.io/py/compressed-segmentation.svg)](https://badge.fury.io/py/compressed-segmentation) 
+
+# Compress Seg [![Picture](https://raw.github.com/janelia-flyem/janelia-flyem.github.com/master/images/HHMI_Janelia_Color_Alternate_180x40.png)](http://www.janelia.org)
+## Library for compressing and decompressing image segmentation (adapted from [neuroglancer](https://github.com/google/neuroglancer))
+
+```python
+import compressed_segmentation as cseg
+
+sx, sy, sz = (128,128,128)
+dtype = np.uint64
+order = 'C'
+
+labels = np.arange(0, sx*sy*sz, dtype=dtype).reshape((sx,sy,sz), order=order)
+compressed = cseg.compress(labels, order=order)
+recovered = cseg.decompress(
+    compressed, (sx,sy,sz) dtype=dtype, order=order
+)
+
+arr = CompressedSegmentationArray(
+    compressed, shape=(sx,sy,sz), dtype=dtype
+)
+label = arr[54,32,103] # random access to single voxels w/o decompressing
+uniq_labels = arr.labels() # get all distinct values w/o decompressing
+binary2 = arr.remap({ 1: 2 }, preserve_missing_labels=False) # remap labels in segmentation w/o decompressing
+recovered = arr.numpy() # decompress to a numpy array, same as decompress
+124213 in arr # test if a value is in the array
+```
+
+```bash
+cseg compress connectomics.npy
+cseg decompress connectomics.npy.cseg --volume-size 512,512,512 --bytes 4
+````
+
+
+NOTE: This repository is the PyPI distribution repo but is based on work done by Jeremy Maitin-Shepard (Google), Stephen Plaza (Janelia Research Campus), and William Silversmith (Princeton) here: https://github.com/janelia-flyem/compressedseg
+
+This library contains routined to decompress and compress segmentation and to manipulate compressed segmentation data defined by the [neuroglancer project](https://github.com/google/neuroglancer/blob/master/src/neuroglancer/sliceview/compressed_segmentation/README.md). compressed_segmentation essentially renumbers large bit width labels to smaller ones in chunks. This provides for large reductions in memory usage and higher compression.
+
+Note that limitations in the compressed_segmentation format restrict the size of the chunk that can be compressed. As this limitation is data dependent, for example a random array with 1024 labels passes testing at 256x256x128, but 256x256x256 often does not.
+
+
+### Features
+
+* Compression and decompression
+* Random access to voxels without decompression
+* Read out unique values without decompression
+* Remap labels without decompression
+* Command line interface for numpy files
+* (TBD) Interface to relabel and manipulate segmentation from the compressed data
+* C++, Python, and Go interface (see original repo for Golang)
+
+### C++ Compilation
+
+Compiling as a shared library. Feel free to subsititute e.g. clang for the C++ compiler.
+
+```bash
+g++ -std=c++11 -O3 -fPIC -shared -I./include src/compress_segmentation.cc src/decompress_segmentation.cc -o compress_segmentation.so
+```
+
+### Python Installation
+
+#### `pip` Binary Installation  
+
+```bash
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+If there are pre-built binaries available for your architecture this should just work. 
+
+#### `pip` Source Installation 
+
+If you need to build from source, you will need to have a C++ compiler installed:
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install numpy
+$ pip install compressed-segmentation
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+#### Direct Installation  
+
+_Requires a C++ compiler such as g++ or clang._
+
+Works with both Python 2 and 3. Encodes from / decodes to 3D or 4D numpy ndarrays.  
+
+```bash
+$ sudo apt-get install g++ python3-dev 
+$ pip install -r requirements.txt
+$ python setup.py install
+
+$ python
+>>> import compressed_segmentation as cseg
+>>> help(cseg)
+```
+
+### License
+
+Please see the licenses in this repo.
+
+
+
+
+
+%prep
+%autosetup -n compressed-segmentation-2.2.0
+
+%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-compressed-segmentation -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..ebfe93d
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+6feccaac84eced12953d6e0485fda5c4  compressed_segmentation-2.2.0.tar.gz