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diff --git a/python-spopt.spec b/python-spopt.spec new file mode 100644 index 0000000..6d56c26 --- /dev/null +++ b/python-spopt.spec @@ -0,0 +1,639 @@ +%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 + + +[](https://github.com/pysal/spopt/actions/workflows/testing.yml) +[](https://codecov.io/gh/pysal/spopt) +[](http://pysal.org/spopt/) +[](https://opensource.org/licenses/BSD-3-Clause) +[](https://github.com/psf/black) +[](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563) +[](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 [](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 + + +[](https://github.com/pysal/spopt/actions/workflows/testing.yml) +[](https://codecov.io/gh/pysal/spopt) +[](http://pysal.org/spopt/) +[](https://opensource.org/licenses/BSD-3-Clause) +[](https://github.com/psf/black) +[](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563) +[](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 [](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 + + +[](https://github.com/pysal/spopt/actions/workflows/testing.yml) +[](https://codecov.io/gh/pysal/spopt) +[](http://pysal.org/spopt/) +[](https://opensource.org/licenses/BSD-3-Clause) +[](https://github.com/psf/black) +[](https://joss.theoj.org/papers/1413cf2c0cf3c561386949f2e1208563) +[](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 [](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 |