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+/spopt-0.5.0.tar.gz
diff --git a/python-spopt.spec b/python-spopt.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-spopt
+Version:	0.5.0
+Release:	1
+Summary:	Spatial Optimization in PySAL
+License:	3-Clause BSD
+URL:		https://github.com/pysal/spopt
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/e5/48/91b44e84f73d9f0e156b79380a0450c732db0097503b401c07d3f8e18813/spopt-0.5.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-geopandas
+Requires:	python3-libpysal
+Requires:	python3-networkx
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-pulp
+Requires:	python3-scikit-learn
+Requires:	python3-scipy
+Requires:	python3-spaghetti
+Requires:	python3-tqdm
+Requires:	python3-black
+Requires:	python3-pre-commit
+Requires:	python3-tqdm
+Requires:	python3-nbsphinx
+Requires:	python3-numpydoc
+Requires:	python3-pandoc
+Requires:	python3-sphinx
+Requires:	python3-sphinxcontrib-bibtex
+Requires:	python3-sphinx-bootstrap-theme
+Requires:	python3-folium
+Requires:	python3-glpk
+Requires:	python3-inequality
+Requires:	python3-matplotlib
+Requires:	python3-matplotlib-scalebar
+Requires:	python3-overpy
+Requires:	python3-routingpy
+Requires:	python3-seaborn
+
+%description
+
+<p align="center">
+<img src="docs/_static/images/pysal_banner.svg" width="370" height="200" />
+</p>
+
+# `spopt`: Spatial Optimization
+
+#### Regionalization, facility location, and transportation-oriented modeling
+
+![tag](https://img.shields.io/github/v/release/pysal/spopt?include_prereleases&sort=semver)
+[![Continuous Integration](https://github.com/pysal/spopt/actions/workflows/testing.yml/badge.svg)](https://github.com/pysal/spopt/actions/workflows/testing.yml)
+[![codecov](https://codecov.io/gh/pysal/spopt/branch/main/graph/badge.svg)](https://codecov.io/gh/pysal/spopt)
+[![Documentation](https://img.shields.io/static/v1.svg?label=docs&message=current&color=9cf)](http://pysal.org/spopt/)
+[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![status](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563/status.svg)](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4444156.svg)](https://doi.org/10.5281/zenodo.4444156)
+
+Spopt is an open-source Python library for solving optimization problems with spatial data. Originating from the `region` module in [PySAL (Python Spatial Analysis Library)](http://pysal.org), it is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions. 
+
+### Regionalization
+
+```python
+import spopt, libpysal, geopandas, numpy
+mexico = geopandas.read_file(libpysal.examples.get_path("mexicojoin.shp"))
+mexico["count"] = 1
+attrs = [f"PCGDP{year}" for year in range(1950, 2010, 10)]
+w = libpysal.weights.Queen.from_dataframe(mexico)
+mexico["count"], threshold_name, threshold, top_n = 1, "count", 4, 2
+numpy.random.seed(123456)
+model = spopt.MaxPHeuristic(mexico, w, attrs, threshold_name, threshold, top_n)
+model.solve()
+mexico["maxp_new"] = model.labels_
+mexico.plot(column="maxp_new", categorical=True, figsize=(12,8), ec="w");
+```
+<p align="center">
+<img src="docs/_static/images/maxp.svg" height="350" />
+</p>
+
+### Locate
+```python
+from spopt.locate import MCLP
+from spopt.locate.util import simulated_geo_points
+import numpy, geopandas, pulp, spaghetti
+
+solver = pulp.PULP_CBC_CMD(msg=False, warmStart=True)
+lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+ntw = spaghetti.Network(in_data=lattice)
+street = spaghetti.element_as_gdf(ntw, arcs=True)
+street_buffered = geopandas.GeoDataFrame(
+    geopandas.GeoSeries(street["geometry"].buffer(0.5).unary_union),
+    crs=street.crs,
+    columns=["geometry"],
+)
+client_points = simulated_geo_points(street_buffered, needed=100, seed=5)
+ntw.snapobservations(client_points, "clients", attribute=True)
+clients_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="clients", snapped=True
+)
+facility_points = simulated_geo_points(street_buffered, needed=10, seed=6)
+ntw.snapobservations(facility_points, "facilities", attribute=True)
+facilities_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="facilities", snapped=True
+)
+cost_matrix = ntw.allneighbordistances(
+    sourcepattern=ntw.pointpatterns["clients"],
+    destpattern=ntw.pointpatterns["facilities"],
+)
+numpy.random.seed(0)
+ai = numpy.random.randint(1, 12, 100)
+mclp_from_cost_matrix = MCLP.from_cost_matrix(cost_matrix, ai, 4, p_facilities=4)
+mclp_from_cost_matrix = mclp_from_cost_matrix.solve(solver)
+```
+*see [notebook](https://github.com/pysal/spopt/blob/main/notebooks/mclp.ipynb) for plotting code*
+<p align="center">
+<img src="docs/_static/images/mclp.png" height="350" />
+</p>
+
+## Examples
+More examples can be found in the [Tutorials](https://pysal.org/spopt/tutorials.html) section of the documentation.
+- [Max-p-regions problem](https://pysal.org/spopt/notebooks/maxp.html)
+- [Skater](https://pysal.org/spopt/notebooks/skater.html)
+- [Region K means](https://pysal.org/spopt/notebooks/reg-k-means.html)
+- [Facility Location Real World Problem](https://pysal.org/spopt/notebooks/facloc-real-world.html)
+
+All examples can be run interactively by launching this repository as a [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pysal/spopt/main).
+
+## Requirements
+- [scipy](http://scipy.github.io/devdocs/)
+- [numpy](https://numpy.org/devdocs/)
+- [pandas](https://pandas.pydata.org/docs/)
+- [networkx](https://networkx.org/)
+- [libpysal](https://pysal.org/libpysal/)
+- [scikit-learn](https://scikit-learn.org/stable/)
+- [geopandas](https://geopandas.org/)
+- [pulp](https://coin-or.github.io/pulp/)
+- [spaghetti](https://github.com/pysal/spaghetti)
+
+## Installation
+spopt is available on the [Python Package Index](https://pypi.org/). Therefore, you can either install directly with pip from the command line:
+```
+$ pip install -U spopt
+```
+or download the source distribution (.tar.gz) and decompress it to your selected destination. Open a command shell and navigate to the decompressed folder. Type:
+```
+$ pip install .
+```
+You may also install the latest stable spopt via conda-forge channel by running:
+```
+$ conda install --channel conda-forge spopt
+```
+
+## Related packages
+
+* Region
+* Locate
+  * [`allagash`](https://github.com/apulverizer/allagash)
+  * [`maximum-coverage-location`](https://github.com/cyang-kth/maximum-coverage-location)
+  * [`p-center`](https://github.com/antoniomedrano/p-center)
+  * [`pyspatialopt`](https://github.com/apulverizer/pyspatialopt)
+
+## Contribute
+
+PySAL-spopt is under active development and contributors are welcome.
+
+If you have any suggestions, feature requests, or bug reports, please open new [issues](https://github.com/pysal/spopt/issues) on GitHub. To submit patches, please review [PySAL's documentation for developers](https://pysal.org/docs/devs/), the PySAL [development guidelines](https://github.com/pysal/pysal/wiki), the `spopt` [contributing guidelines](https://github.com/pysal/spopt/blob/main/.github/CONTRIBUTING.md) before  opening a [pull request](https://github.com/pysal/spopt/pulls). Once your changes get merged, you’ll automatically be added to the [Contributors List](https://github.com/pysal/spopt/graphs/contributors).
+
+
+## Support
+If you are having trouble, please [create an issue](https://github.com/pysal/spopt/issues), [start a discussion](https://github.com/pysal/spopt/discussions), or talk to us in the [gitter room](https://gitter.im/pysal/spopt).
+
+## Code of Conduct
+
+As a PySAL-federated project, `spopt` follows the [Code of Conduct](https://github.com/pysal/governance/blob/main/conduct/code_of_conduct.rst) under the [PySAL governance model](https://github.com/pysal/governance).
+
+
+## License
+
+The project is licensed under the [BSD 3-Clause license](https://github.com/pysal/spopt/blob/main/LICENSE.txt).
+
+
+## Citation
+
+If you use PySAL-spopt in a scientific publication, we would appreciate using the following citations:
+
+```
+@misc{spopt2021,
+    author    = {Feng, Xin, and Gaboardi, James D. and Knaap, Elijah and
+                Rey, Sergio J. and Wei, Ran},
+    month     = {jan},
+    year      = {2021},
+    title     = {pysal/spopt},
+    url       = {https://github.com/pysal/spopt},
+    doi       = {10.5281/zenodo.4444156},
+    keywords  = {python,regionalization,spatial-optimization,location-modeling}
+}
+
+@article{spopt2022,
+    author    = {Feng, Xin and Barcelos, Germano and Gaboardi, James D. and
+                Knaap, Elijah and Wei, Ran and Wolf, Levi J. and
+                Zhao, Qunshan and Rey, Sergio J.},
+    year      = {2022},
+    title     = {spopt: a python package for solving spatial optimization problems in PySAL},
+    journal   = {Journal of Open Source Software},
+    publisher = {The Open Journal},
+    volume    = {7},
+    number    = {74},
+    pages     = {3330},
+    url       = {https://doi.org/10.21105/joss.03330},
+    doi       = {10.21105/joss.03330},
+}
+```
+
+## Funding
+
+This project is/was partially funded through:
+
+[<img align="middle" src="docs/_static/images/nsf_logo.png" width="75">](https://www.nsf.gov/index.jsp) National Science Foundation Award #1831615: [RIDIR: Scalable Geospatial Analytics for Social Science Research](https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831615)
+
+<!-- [<img align="middle" src="docs/_static/image/IMAGE2.png" width="150">](link2) Some text2: [Project title 2](another_link2) -->
+
+
+%package -n python3-spopt
+Summary:	Spatial Optimization in PySAL
+Provides:	python-spopt
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-spopt
+
+<p align="center">
+<img src="docs/_static/images/pysal_banner.svg" width="370" height="200" />
+</p>
+
+# `spopt`: Spatial Optimization
+
+#### Regionalization, facility location, and transportation-oriented modeling
+
+![tag](https://img.shields.io/github/v/release/pysal/spopt?include_prereleases&sort=semver)
+[![Continuous Integration](https://github.com/pysal/spopt/actions/workflows/testing.yml/badge.svg)](https://github.com/pysal/spopt/actions/workflows/testing.yml)
+[![codecov](https://codecov.io/gh/pysal/spopt/branch/main/graph/badge.svg)](https://codecov.io/gh/pysal/spopt)
+[![Documentation](https://img.shields.io/static/v1.svg?label=docs&message=current&color=9cf)](http://pysal.org/spopt/)
+[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![status](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563/status.svg)](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4444156.svg)](https://doi.org/10.5281/zenodo.4444156)
+
+Spopt is an open-source Python library for solving optimization problems with spatial data. Originating from the `region` module in [PySAL (Python Spatial Analysis Library)](http://pysal.org), it is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions. 
+
+### Regionalization
+
+```python
+import spopt, libpysal, geopandas, numpy
+mexico = geopandas.read_file(libpysal.examples.get_path("mexicojoin.shp"))
+mexico["count"] = 1
+attrs = [f"PCGDP{year}" for year in range(1950, 2010, 10)]
+w = libpysal.weights.Queen.from_dataframe(mexico)
+mexico["count"], threshold_name, threshold, top_n = 1, "count", 4, 2
+numpy.random.seed(123456)
+model = spopt.MaxPHeuristic(mexico, w, attrs, threshold_name, threshold, top_n)
+model.solve()
+mexico["maxp_new"] = model.labels_
+mexico.plot(column="maxp_new", categorical=True, figsize=(12,8), ec="w");
+```
+<p align="center">
+<img src="docs/_static/images/maxp.svg" height="350" />
+</p>
+
+### Locate
+```python
+from spopt.locate import MCLP
+from spopt.locate.util import simulated_geo_points
+import numpy, geopandas, pulp, spaghetti
+
+solver = pulp.PULP_CBC_CMD(msg=False, warmStart=True)
+lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+ntw = spaghetti.Network(in_data=lattice)
+street = spaghetti.element_as_gdf(ntw, arcs=True)
+street_buffered = geopandas.GeoDataFrame(
+    geopandas.GeoSeries(street["geometry"].buffer(0.5).unary_union),
+    crs=street.crs,
+    columns=["geometry"],
+)
+client_points = simulated_geo_points(street_buffered, needed=100, seed=5)
+ntw.snapobservations(client_points, "clients", attribute=True)
+clients_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="clients", snapped=True
+)
+facility_points = simulated_geo_points(street_buffered, needed=10, seed=6)
+ntw.snapobservations(facility_points, "facilities", attribute=True)
+facilities_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="facilities", snapped=True
+)
+cost_matrix = ntw.allneighbordistances(
+    sourcepattern=ntw.pointpatterns["clients"],
+    destpattern=ntw.pointpatterns["facilities"],
+)
+numpy.random.seed(0)
+ai = numpy.random.randint(1, 12, 100)
+mclp_from_cost_matrix = MCLP.from_cost_matrix(cost_matrix, ai, 4, p_facilities=4)
+mclp_from_cost_matrix = mclp_from_cost_matrix.solve(solver)
+```
+*see [notebook](https://github.com/pysal/spopt/blob/main/notebooks/mclp.ipynb) for plotting code*
+<p align="center">
+<img src="docs/_static/images/mclp.png" height="350" />
+</p>
+
+## Examples
+More examples can be found in the [Tutorials](https://pysal.org/spopt/tutorials.html) section of the documentation.
+- [Max-p-regions problem](https://pysal.org/spopt/notebooks/maxp.html)
+- [Skater](https://pysal.org/spopt/notebooks/skater.html)
+- [Region K means](https://pysal.org/spopt/notebooks/reg-k-means.html)
+- [Facility Location Real World Problem](https://pysal.org/spopt/notebooks/facloc-real-world.html)
+
+All examples can be run interactively by launching this repository as a [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pysal/spopt/main).
+
+## Requirements
+- [scipy](http://scipy.github.io/devdocs/)
+- [numpy](https://numpy.org/devdocs/)
+- [pandas](https://pandas.pydata.org/docs/)
+- [networkx](https://networkx.org/)
+- [libpysal](https://pysal.org/libpysal/)
+- [scikit-learn](https://scikit-learn.org/stable/)
+- [geopandas](https://geopandas.org/)
+- [pulp](https://coin-or.github.io/pulp/)
+- [spaghetti](https://github.com/pysal/spaghetti)
+
+## Installation
+spopt is available on the [Python Package Index](https://pypi.org/). Therefore, you can either install directly with pip from the command line:
+```
+$ pip install -U spopt
+```
+or download the source distribution (.tar.gz) and decompress it to your selected destination. Open a command shell and navigate to the decompressed folder. Type:
+```
+$ pip install .
+```
+You may also install the latest stable spopt via conda-forge channel by running:
+```
+$ conda install --channel conda-forge spopt
+```
+
+## Related packages
+
+* Region
+* Locate
+  * [`allagash`](https://github.com/apulverizer/allagash)
+  * [`maximum-coverage-location`](https://github.com/cyang-kth/maximum-coverage-location)
+  * [`p-center`](https://github.com/antoniomedrano/p-center)
+  * [`pyspatialopt`](https://github.com/apulverizer/pyspatialopt)
+
+## Contribute
+
+PySAL-spopt is under active development and contributors are welcome.
+
+If you have any suggestions, feature requests, or bug reports, please open new [issues](https://github.com/pysal/spopt/issues) on GitHub. To submit patches, please review [PySAL's documentation for developers](https://pysal.org/docs/devs/), the PySAL [development guidelines](https://github.com/pysal/pysal/wiki), the `spopt` [contributing guidelines](https://github.com/pysal/spopt/blob/main/.github/CONTRIBUTING.md) before  opening a [pull request](https://github.com/pysal/spopt/pulls). Once your changes get merged, you’ll automatically be added to the [Contributors List](https://github.com/pysal/spopt/graphs/contributors).
+
+
+## Support
+If you are having trouble, please [create an issue](https://github.com/pysal/spopt/issues), [start a discussion](https://github.com/pysal/spopt/discussions), or talk to us in the [gitter room](https://gitter.im/pysal/spopt).
+
+## Code of Conduct
+
+As a PySAL-federated project, `spopt` follows the [Code of Conduct](https://github.com/pysal/governance/blob/main/conduct/code_of_conduct.rst) under the [PySAL governance model](https://github.com/pysal/governance).
+
+
+## License
+
+The project is licensed under the [BSD 3-Clause license](https://github.com/pysal/spopt/blob/main/LICENSE.txt).
+
+
+## Citation
+
+If you use PySAL-spopt in a scientific publication, we would appreciate using the following citations:
+
+```
+@misc{spopt2021,
+    author    = {Feng, Xin, and Gaboardi, James D. and Knaap, Elijah and
+                Rey, Sergio J. and Wei, Ran},
+    month     = {jan},
+    year      = {2021},
+    title     = {pysal/spopt},
+    url       = {https://github.com/pysal/spopt},
+    doi       = {10.5281/zenodo.4444156},
+    keywords  = {python,regionalization,spatial-optimization,location-modeling}
+}
+
+@article{spopt2022,
+    author    = {Feng, Xin and Barcelos, Germano and Gaboardi, James D. and
+                Knaap, Elijah and Wei, Ran and Wolf, Levi J. and
+                Zhao, Qunshan and Rey, Sergio J.},
+    year      = {2022},
+    title     = {spopt: a python package for solving spatial optimization problems in PySAL},
+    journal   = {Journal of Open Source Software},
+    publisher = {The Open Journal},
+    volume    = {7},
+    number    = {74},
+    pages     = {3330},
+    url       = {https://doi.org/10.21105/joss.03330},
+    doi       = {10.21105/joss.03330},
+}
+```
+
+## Funding
+
+This project is/was partially funded through:
+
+[<img align="middle" src="docs/_static/images/nsf_logo.png" width="75">](https://www.nsf.gov/index.jsp) National Science Foundation Award #1831615: [RIDIR: Scalable Geospatial Analytics for Social Science Research](https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831615)
+
+<!-- [<img align="middle" src="docs/_static/image/IMAGE2.png" width="150">](link2) Some text2: [Project title 2](another_link2) -->
+
+
+%package help
+Summary:	Development documents and examples for spopt
+Provides:	python3-spopt-doc
+%description help
+
+<p align="center">
+<img src="docs/_static/images/pysal_banner.svg" width="370" height="200" />
+</p>
+
+# `spopt`: Spatial Optimization
+
+#### Regionalization, facility location, and transportation-oriented modeling
+
+![tag](https://img.shields.io/github/v/release/pysal/spopt?include_prereleases&sort=semver)
+[![Continuous Integration](https://github.com/pysal/spopt/actions/workflows/testing.yml/badge.svg)](https://github.com/pysal/spopt/actions/workflows/testing.yml)
+[![codecov](https://codecov.io/gh/pysal/spopt/branch/main/graph/badge.svg)](https://codecov.io/gh/pysal/spopt)
+[![Documentation](https://img.shields.io/static/v1.svg?label=docs&message=current&color=9cf)](http://pysal.org/spopt/)
+[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![status](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563/status.svg)](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4444156.svg)](https://doi.org/10.5281/zenodo.4444156)
+
+Spopt is an open-source Python library for solving optimization problems with spatial data. Originating from the `region` module in [PySAL (Python Spatial Analysis Library)](http://pysal.org), it is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions. 
+
+### Regionalization
+
+```python
+import spopt, libpysal, geopandas, numpy
+mexico = geopandas.read_file(libpysal.examples.get_path("mexicojoin.shp"))
+mexico["count"] = 1
+attrs = [f"PCGDP{year}" for year in range(1950, 2010, 10)]
+w = libpysal.weights.Queen.from_dataframe(mexico)
+mexico["count"], threshold_name, threshold, top_n = 1, "count", 4, 2
+numpy.random.seed(123456)
+model = spopt.MaxPHeuristic(mexico, w, attrs, threshold_name, threshold, top_n)
+model.solve()
+mexico["maxp_new"] = model.labels_
+mexico.plot(column="maxp_new", categorical=True, figsize=(12,8), ec="w");
+```
+<p align="center">
+<img src="docs/_static/images/maxp.svg" height="350" />
+</p>
+
+### Locate
+```python
+from spopt.locate import MCLP
+from spopt.locate.util import simulated_geo_points
+import numpy, geopandas, pulp, spaghetti
+
+solver = pulp.PULP_CBC_CMD(msg=False, warmStart=True)
+lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+ntw = spaghetti.Network(in_data=lattice)
+street = spaghetti.element_as_gdf(ntw, arcs=True)
+street_buffered = geopandas.GeoDataFrame(
+    geopandas.GeoSeries(street["geometry"].buffer(0.5).unary_union),
+    crs=street.crs,
+    columns=["geometry"],
+)
+client_points = simulated_geo_points(street_buffered, needed=100, seed=5)
+ntw.snapobservations(client_points, "clients", attribute=True)
+clients_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="clients", snapped=True
+)
+facility_points = simulated_geo_points(street_buffered, needed=10, seed=6)
+ntw.snapobservations(facility_points, "facilities", attribute=True)
+facilities_snapped = spaghetti.element_as_gdf(
+    ntw, pp_name="facilities", snapped=True
+)
+cost_matrix = ntw.allneighbordistances(
+    sourcepattern=ntw.pointpatterns["clients"],
+    destpattern=ntw.pointpatterns["facilities"],
+)
+numpy.random.seed(0)
+ai = numpy.random.randint(1, 12, 100)
+mclp_from_cost_matrix = MCLP.from_cost_matrix(cost_matrix, ai, 4, p_facilities=4)
+mclp_from_cost_matrix = mclp_from_cost_matrix.solve(solver)
+```
+*see [notebook](https://github.com/pysal/spopt/blob/main/notebooks/mclp.ipynb) for plotting code*
+<p align="center">
+<img src="docs/_static/images/mclp.png" height="350" />
+</p>
+
+## Examples
+More examples can be found in the [Tutorials](https://pysal.org/spopt/tutorials.html) section of the documentation.
+- [Max-p-regions problem](https://pysal.org/spopt/notebooks/maxp.html)
+- [Skater](https://pysal.org/spopt/notebooks/skater.html)
+- [Region K means](https://pysal.org/spopt/notebooks/reg-k-means.html)
+- [Facility Location Real World Problem](https://pysal.org/spopt/notebooks/facloc-real-world.html)
+
+All examples can be run interactively by launching this repository as a [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pysal/spopt/main).
+
+## Requirements
+- [scipy](http://scipy.github.io/devdocs/)
+- [numpy](https://numpy.org/devdocs/)
+- [pandas](https://pandas.pydata.org/docs/)
+- [networkx](https://networkx.org/)
+- [libpysal](https://pysal.org/libpysal/)
+- [scikit-learn](https://scikit-learn.org/stable/)
+- [geopandas](https://geopandas.org/)
+- [pulp](https://coin-or.github.io/pulp/)
+- [spaghetti](https://github.com/pysal/spaghetti)
+
+## Installation
+spopt is available on the [Python Package Index](https://pypi.org/). Therefore, you can either install directly with pip from the command line:
+```
+$ pip install -U spopt
+```
+or download the source distribution (.tar.gz) and decompress it to your selected destination. Open a command shell and navigate to the decompressed folder. Type:
+```
+$ pip install .
+```
+You may also install the latest stable spopt via conda-forge channel by running:
+```
+$ conda install --channel conda-forge spopt
+```
+
+## Related packages
+
+* Region
+* Locate
+  * [`allagash`](https://github.com/apulverizer/allagash)
+  * [`maximum-coverage-location`](https://github.com/cyang-kth/maximum-coverage-location)
+  * [`p-center`](https://github.com/antoniomedrano/p-center)
+  * [`pyspatialopt`](https://github.com/apulverizer/pyspatialopt)
+
+## Contribute
+
+PySAL-spopt is under active development and contributors are welcome.
+
+If you have any suggestions, feature requests, or bug reports, please open new [issues](https://github.com/pysal/spopt/issues) on GitHub. To submit patches, please review [PySAL's documentation for developers](https://pysal.org/docs/devs/), the PySAL [development guidelines](https://github.com/pysal/pysal/wiki), the `spopt` [contributing guidelines](https://github.com/pysal/spopt/blob/main/.github/CONTRIBUTING.md) before  opening a [pull request](https://github.com/pysal/spopt/pulls). Once your changes get merged, you’ll automatically be added to the [Contributors List](https://github.com/pysal/spopt/graphs/contributors).
+
+
+## Support
+If you are having trouble, please [create an issue](https://github.com/pysal/spopt/issues), [start a discussion](https://github.com/pysal/spopt/discussions), or talk to us in the [gitter room](https://gitter.im/pysal/spopt).
+
+## Code of Conduct
+
+As a PySAL-federated project, `spopt` follows the [Code of Conduct](https://github.com/pysal/governance/blob/main/conduct/code_of_conduct.rst) under the [PySAL governance model](https://github.com/pysal/governance).
+
+
+## License
+
+The project is licensed under the [BSD 3-Clause license](https://github.com/pysal/spopt/blob/main/LICENSE.txt).
+
+
+## Citation
+
+If you use PySAL-spopt in a scientific publication, we would appreciate using the following citations:
+
+```
+@misc{spopt2021,
+    author    = {Feng, Xin, and Gaboardi, James D. and Knaap, Elijah and
+                Rey, Sergio J. and Wei, Ran},
+    month     = {jan},
+    year      = {2021},
+    title     = {pysal/spopt},
+    url       = {https://github.com/pysal/spopt},
+    doi       = {10.5281/zenodo.4444156},
+    keywords  = {python,regionalization,spatial-optimization,location-modeling}
+}
+
+@article{spopt2022,
+    author    = {Feng, Xin and Barcelos, Germano and Gaboardi, James D. and
+                Knaap, Elijah and Wei, Ran and Wolf, Levi J. and
+                Zhao, Qunshan and Rey, Sergio J.},
+    year      = {2022},
+    title     = {spopt: a python package for solving spatial optimization problems in PySAL},
+    journal   = {Journal of Open Source Software},
+    publisher = {The Open Journal},
+    volume    = {7},
+    number    = {74},
+    pages     = {3330},
+    url       = {https://doi.org/10.21105/joss.03330},
+    doi       = {10.21105/joss.03330},
+}
+```
+
+## Funding
+
+This project is/was partially funded through:
+
+[<img align="middle" src="docs/_static/images/nsf_logo.png" width="75">](https://www.nsf.gov/index.jsp) National Science Foundation Award #1831615: [RIDIR: Scalable Geospatial Analytics for Social Science Research](https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831615)
+
+<!-- [<img align="middle" src="docs/_static/image/IMAGE2.png" width="150">](link2) Some text2: [Project title 2](another_link2) -->
+
+
+%prep
+%autosetup -n spopt-0.5.0
+
+%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-spopt -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..6e04e6a
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+85ff634844243144b2b882d280a6e60d  spopt-0.5.0.tar.gz