automatic import of python-scimapopeneuler20.03

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diff --git a/.gitignore b/.gitignore
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+/scimap-1.1.0.tar.gz
diff --git a/python-scimap.spec b/python-scimap.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-scimap
+Version:	1.1.0
+Release:	1
+Summary:	Spatial Single-Cell Analysis Toolkit
+License:	MIT
+URL:		https://pypi.org/project/scimap/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/dc/df/9fbc541d80ff9ced659aa755c8bc0107a29bb1e4d20f97928b3691bc64aa/scimap-1.1.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-pytest
+Requires:	python3-anndata
+Requires:	python3-pandas
+Requires:	python3-scipy
+Requires:	python3-seaborn
+Requires:	python3-tifffile
+Requires:	python3-numpy
+Requires:	python3-pytest-xvfb
+Requires:	python3-matplotlib
+Requires:	python3-PhenoGraph
+Requires:	python3-scanpy
+Requires:	python3-mkdocs
+Requires:	python3-plotly
+Requires:	python3-TiffFile
+Requires:	python3-dask[array]
+Requires:	python3-zarr
+Requires:	python3-napari
+Requires:	python3-numba
+Requires:	python3-shapely
+Requires:	python3-gensim
+Requires:	python3-mkdocs-material
+Requires:	python3-napari-ome-zarr
+Requires:	python3-llvmlite
+Requires:	python3-combat
+
+%description
+# Single-Cell Image Analysis Package
+<br>
+
+[![build: Unix-Mac-Win](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml)
+[![Docs](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml)
+[![Downloads](https://pepy.tech/badge/scimap)](https://pepy.tech/project/scimap)
+[![PyPI Version](https://img.shields.io/pypi/v/scimap.svg)](https://pypi.org/project/scimap)
+[![PyPI License](https://img.shields.io/pypi/l/scimap.svg)](https://pypi.org/project/scimap)
+[![Gitter chat](https://badges.gitter.im/scimap_io/community.png)](https://gitter.im/scimap_io/community)
+[![DOI](https://zenodo.org/badge/271099296.svg)](https://zenodo.org/badge/latestdoi/271099296)
+
+<br>
+
+<img src="./docs/assets/scimap_logo.jpg" style="max-width:700px;width:100%" >
+
+<br> 
+
+Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.
+
+## Installation
+
+We strongly recommend installing `scimap` in a fresh virtual environment.
+
+```
+# If you have conda installed
+conda create --name scimap python=3.8
+conda activate scimap
+```
+
+Install `scimap` directly into an activated virtual environment:
+
+```python
+$ pip install scimap
+```
+
+After installation, the package can be imported as:
+
+```python
+$ python
+>>> import scimap as sm
+```
+
+
+## Get Started
+
+
+#### Detailed documentation of `scimap` functions and tutorials are available [here](http://scimap.xyz/).
+
+*SCIMAP* development is led by [Ajit Johnson Nirmal](https://ajitjohnson.com/) at the Laboratory of Systems Pharmacology, Harvard Medical School.
+
+## Funding
+This work is supported by the following NIH grant K99-CA256497
+
+
+
+%package -n python3-scimap
+Summary:	Spatial Single-Cell Analysis Toolkit
+Provides:	python-scimap
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-scimap
+# Single-Cell Image Analysis Package
+<br>
+
+[![build: Unix-Mac-Win](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml)
+[![Docs](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml)
+[![Downloads](https://pepy.tech/badge/scimap)](https://pepy.tech/project/scimap)
+[![PyPI Version](https://img.shields.io/pypi/v/scimap.svg)](https://pypi.org/project/scimap)
+[![PyPI License](https://img.shields.io/pypi/l/scimap.svg)](https://pypi.org/project/scimap)
+[![Gitter chat](https://badges.gitter.im/scimap_io/community.png)](https://gitter.im/scimap_io/community)
+[![DOI](https://zenodo.org/badge/271099296.svg)](https://zenodo.org/badge/latestdoi/271099296)
+
+<br>
+
+<img src="./docs/assets/scimap_logo.jpg" style="max-width:700px;width:100%" >
+
+<br> 
+
+Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.
+
+## Installation
+
+We strongly recommend installing `scimap` in a fresh virtual environment.
+
+```
+# If you have conda installed
+conda create --name scimap python=3.8
+conda activate scimap
+```
+
+Install `scimap` directly into an activated virtual environment:
+
+```python
+$ pip install scimap
+```
+
+After installation, the package can be imported as:
+
+```python
+$ python
+>>> import scimap as sm
+```
+
+
+## Get Started
+
+
+#### Detailed documentation of `scimap` functions and tutorials are available [here](http://scimap.xyz/).
+
+*SCIMAP* development is led by [Ajit Johnson Nirmal](https://ajitjohnson.com/) at the Laboratory of Systems Pharmacology, Harvard Medical School.
+
+## Funding
+This work is supported by the following NIH grant K99-CA256497
+
+
+
+%package help
+Summary:	Development documents and examples for scimap
+Provides:	python3-scimap-doc
+%description help
+# Single-Cell Image Analysis Package
+<br>
+
+[![build: Unix-Mac-Win](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/build-unix-mac-win.yml)
+[![Docs](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml/badge.svg)](https://github.com/ajitjohnson/scimap/actions/workflows/docs.yml)
+[![Downloads](https://pepy.tech/badge/scimap)](https://pepy.tech/project/scimap)
+[![PyPI Version](https://img.shields.io/pypi/v/scimap.svg)](https://pypi.org/project/scimap)
+[![PyPI License](https://img.shields.io/pypi/l/scimap.svg)](https://pypi.org/project/scimap)
+[![Gitter chat](https://badges.gitter.im/scimap_io/community.png)](https://gitter.im/scimap_io/community)
+[![DOI](https://zenodo.org/badge/271099296.svg)](https://zenodo.org/badge/latestdoi/271099296)
+
+<br>
+
+<img src="./docs/assets/scimap_logo.jpg" style="max-width:700px;width:100%" >
+
+<br> 
+
+Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spatial datasets mapped to XY coordinates. The package uses the [anndata](https://anndata.readthedocs.io/en/stable/anndata.AnnData.html) framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. The Python-based implementation efficiently deals with large datasets of millions of cells.
+
+## Installation
+
+We strongly recommend installing `scimap` in a fresh virtual environment.
+
+```
+# If you have conda installed
+conda create --name scimap python=3.8
+conda activate scimap
+```
+
+Install `scimap` directly into an activated virtual environment:
+
+```python
+$ pip install scimap
+```
+
+After installation, the package can be imported as:
+
+```python
+$ python
+>>> import scimap as sm
+```
+
+
+## Get Started
+
+
+#### Detailed documentation of `scimap` functions and tutorials are available [here](http://scimap.xyz/).
+
+*SCIMAP* development is led by [Ajit Johnson Nirmal](https://ajitjohnson.com/) at the Laboratory of Systems Pharmacology, Harvard Medical School.
+
+## Funding
+This work is supported by the following NIH grant K99-CA256497
+
+
+
+%prep
+%autosetup -n scimap-1.1.0
+
+%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-scimap -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..d209c70
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+++ b/sources
@@ -0,0 +1 @@
+c47ccdf5335273c8049302fa84c3ac92  scimap-1.1.0.tar.gz