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diff --git a/python-simplification.spec b/python-simplification.spec new file mode 100644 index 0000000..209835e --- /dev/null +++ b/python-simplification.spec @@ -0,0 +1,465 @@ +%global _empty_manifest_terminate_build 0 +Name: python-simplification +Version: 0.6.7 +Release: 1 +Summary: Fast linestring simplification using RDP or Visvalingam-Whyatt and a Rust binary +License: MIT +URL: https://github.com/urschrei/simplification +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/3b/ed/292be02012d33ccd64b71653bb7e302bac7305092e1df7605bd8e8d4328a/simplification-0.6.7.tar.gz + +Requires: python3-numpy +Requires: python3-pytest +Requires: python3-numpy +Requires: python3-pytest + +%description +[](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [](https://coveralls.io/github/urschrei/simplification?branch=master) [](https://pepy.tech/project/simplification)[](https://zenodo.org/badge/latestdoi/65199659) + +# Simplification +Simplify a LineString using the [Ramer–Douglas–Peucker](https://en.wikipedia.org/wiki/Ramer–Douglas–Peucker_algorithm) or [Visvalingam-Whyatt](https://bost.ocks.org/mike/simplify/) algorithms + + + +## Installation +`pip install simplification` +Please use a recent (>= 8.1.2) version of `pip`. + +### Supported Python Versions (Linux x86_64 + aarch64, macOS x86_64 + arm64, Windows amd64) +- Python 3.7 +- Python 3.8 +- Python 3.9 +- Python 3.10 +- Python 3.11 + +### Supported Platforms +- Linux (`manylinux`-compatible) x86_64 and aarch64 +- macOS Darwin x86_64 and arm64 +- Windows 64-bit + +## Usage +```python +from simplification.cutil import ( + simplify_coords, + simplify_coords_idx, + simplify_coords_vw, + simplify_coords_vw_idx, + simplify_coords_vwp, +) + +# Using Ramer–Douglas–Peucker +coords = [ + [0.0, 0.0], + [5.0, 4.0], + [11.0, 5.5], + [17.3, 3.2], + [27.8, 0.1] +] + +# For RDP, Try an epsilon of 1.0 to start with. Other sensible values include 0.01, 0.001 +simplified = simplify_coords(coords, 1.0) + +# simplified is [[0.0, 0.0], [5.0, 4.0], [11.0, 5.5], [27.8, 0.1]] + +# Using Visvalingam-Whyatt +# You can also pass numpy arrays, in which case you'll get numpy arrays back +import numpy as np +coords_vw = np.array([ + [5.0, 2.0], + [3.0, 8.0], + [6.0, 20.0], + [7.0, 25.0], + [10.0, 10.0] +]) +simplified_vw = simplify_coords_vw(coords_vw, 30.0) + +# simplified_vw is [[5.0, 2.0], [7.0, 25.0], [10.0, 10.0]] +``` + +Passing empty and/or 1-element lists will return them unaltered. + +## But I only want the simplified **Indices** +`simplification` now has: + +- `cutil.simplify_coords_idx` +- `cutil.simplify_coords_vw_idx` + +The values returned by these functions are the **retained** indices. In order to use them as e.g. a [masked array](https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html#what-is-a-masked-array) in Numpy, something like the following will work: + + import numpy as np + from simplification.cutil import simplify_coords_idx + + # assume an array of coordinates: orig + simplified = simplify_coords_idx(orig, 1.0) + # build new geometry using only retained coordinates + orig_simplified = orig[simplified] + + +## But I need to ensure that the resulting geometries are valid +You can use the topology-preserving variant of `VW` for this: `simplify_coords_vwp`. It's slower, but has a far greater likelihood of producing a valid geometry. + + +## But I Want to Simplify Polylines +No problem; [Decode them to LineStrings](https://github.com/urschrei/pypolyline) first. + +``` python +# pip install pypolyline before you do this +from pypolyline.cutil import decode_polyline +# an iterable of Google-encoded Polylines, so precision is 5. For OSRM &c., it's 6 +decoded = (decode_polyline(line, 5) for line in polylines) +simplified = [simplify_coords(line, 1.0) for line in decoded] +``` + +## How it Works +FFI and a [Rust binary](https://github.com/urschrei/rdp) + +## Is It Fast +I should think so. +### What does that mean +Using `numpy` arrays for input and output, the library can be reasonably expected to process around 2500 1000-point LineStrings per second on a Core i7 or equivalent, for a 98%+ reduction in size. +A larger LineString, containing 200k+ points can be reduced to around 3k points (98.5%+) in around 50ms using RDP. + +This is based on a test harness available [here](benchmark_runner.py). +#### Disclaimer +All benchmarks are subjective, and pathological input will greatly increase processing time. Error-checking is non-existent at this point. + +## License +[MIT](license.txt) + +## Citing `Simplification` +If Simplification has been significant in your research, and you would like to acknowledge the project in your academic publication, we suggest citing it as follows (example in APA style, 7th edition): + +> Hügel, S. (2021). Simplification (Version X.Y.Z) [Computer software]. https://doi.org/10.5281/zenodo.5774852 + +In Bibtex format: + + @software{Hugel_Simplification_2021, + author = {Hügel, Stephan}, + doi = {10.5281/zenodo.5774852}, + license = {MIT}, + month = {12}, + title = {{Simplification}}, + url = {https://github.com/urschrei/simplification}, + version = {X.Y.Z}, + year = {2021} + } + + +%package -n python3-simplification +Summary: Fast linestring simplification using RDP or Visvalingam-Whyatt and a Rust binary +Provides: python-simplification +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +BuildRequires: python3-cffi +BuildRequires: gcc +BuildRequires: gdb +%description -n python3-simplification +[](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [](https://coveralls.io/github/urschrei/simplification?branch=master) [](https://pepy.tech/project/simplification)[](https://zenodo.org/badge/latestdoi/65199659) + +# Simplification +Simplify a LineString using the [Ramer–Douglas–Peucker](https://en.wikipedia.org/wiki/Ramer–Douglas–Peucker_algorithm) or [Visvalingam-Whyatt](https://bost.ocks.org/mike/simplify/) algorithms + + + +## Installation +`pip install simplification` +Please use a recent (>= 8.1.2) version of `pip`. + +### Supported Python Versions (Linux x86_64 + aarch64, macOS x86_64 + arm64, Windows amd64) +- Python 3.7 +- Python 3.8 +- Python 3.9 +- Python 3.10 +- Python 3.11 + +### Supported Platforms +- Linux (`manylinux`-compatible) x86_64 and aarch64 +- macOS Darwin x86_64 and arm64 +- Windows 64-bit + +## Usage +```python +from simplification.cutil import ( + simplify_coords, + simplify_coords_idx, + simplify_coords_vw, + simplify_coords_vw_idx, + simplify_coords_vwp, +) + +# Using Ramer–Douglas–Peucker +coords = [ + [0.0, 0.0], + [5.0, 4.0], + [11.0, 5.5], + [17.3, 3.2], + [27.8, 0.1] +] + +# For RDP, Try an epsilon of 1.0 to start with. Other sensible values include 0.01, 0.001 +simplified = simplify_coords(coords, 1.0) + +# simplified is [[0.0, 0.0], [5.0, 4.0], [11.0, 5.5], [27.8, 0.1]] + +# Using Visvalingam-Whyatt +# You can also pass numpy arrays, in which case you'll get numpy arrays back +import numpy as np +coords_vw = np.array([ + [5.0, 2.0], + [3.0, 8.0], + [6.0, 20.0], + [7.0, 25.0], + [10.0, 10.0] +]) +simplified_vw = simplify_coords_vw(coords_vw, 30.0) + +# simplified_vw is [[5.0, 2.0], [7.0, 25.0], [10.0, 10.0]] +``` + +Passing empty and/or 1-element lists will return them unaltered. + +## But I only want the simplified **Indices** +`simplification` now has: + +- `cutil.simplify_coords_idx` +- `cutil.simplify_coords_vw_idx` + +The values returned by these functions are the **retained** indices. In order to use them as e.g. a [masked array](https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html#what-is-a-masked-array) in Numpy, something like the following will work: + + import numpy as np + from simplification.cutil import simplify_coords_idx + + # assume an array of coordinates: orig + simplified = simplify_coords_idx(orig, 1.0) + # build new geometry using only retained coordinates + orig_simplified = orig[simplified] + + +## But I need to ensure that the resulting geometries are valid +You can use the topology-preserving variant of `VW` for this: `simplify_coords_vwp`. It's slower, but has a far greater likelihood of producing a valid geometry. + + +## But I Want to Simplify Polylines +No problem; [Decode them to LineStrings](https://github.com/urschrei/pypolyline) first. + +``` python +# pip install pypolyline before you do this +from pypolyline.cutil import decode_polyline +# an iterable of Google-encoded Polylines, so precision is 5. For OSRM &c., it's 6 +decoded = (decode_polyline(line, 5) for line in polylines) +simplified = [simplify_coords(line, 1.0) for line in decoded] +``` + +## How it Works +FFI and a [Rust binary](https://github.com/urschrei/rdp) + +## Is It Fast +I should think so. +### What does that mean +Using `numpy` arrays for input and output, the library can be reasonably expected to process around 2500 1000-point LineStrings per second on a Core i7 or equivalent, for a 98%+ reduction in size. +A larger LineString, containing 200k+ points can be reduced to around 3k points (98.5%+) in around 50ms using RDP. + +This is based on a test harness available [here](benchmark_runner.py). +#### Disclaimer +All benchmarks are subjective, and pathological input will greatly increase processing time. Error-checking is non-existent at this point. + +## License +[MIT](license.txt) + +## Citing `Simplification` +If Simplification has been significant in your research, and you would like to acknowledge the project in your academic publication, we suggest citing it as follows (example in APA style, 7th edition): + +> Hügel, S. (2021). Simplification (Version X.Y.Z) [Computer software]. https://doi.org/10.5281/zenodo.5774852 + +In Bibtex format: + + @software{Hugel_Simplification_2021, + author = {Hügel, Stephan}, + doi = {10.5281/zenodo.5774852}, + license = {MIT}, + month = {12}, + title = {{Simplification}}, + url = {https://github.com/urschrei/simplification}, + version = {X.Y.Z}, + year = {2021} + } + + +%package help +Summary: Development documents and examples for simplification +Provides: python3-simplification-doc +%description help +[](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [](https://coveralls.io/github/urschrei/simplification?branch=master) [](https://pepy.tech/project/simplification)[](https://zenodo.org/badge/latestdoi/65199659) + +# Simplification +Simplify a LineString using the [Ramer–Douglas–Peucker](https://en.wikipedia.org/wiki/Ramer–Douglas–Peucker_algorithm) or [Visvalingam-Whyatt](https://bost.ocks.org/mike/simplify/) algorithms + + + +## Installation +`pip install simplification` +Please use a recent (>= 8.1.2) version of `pip`. + +### Supported Python Versions (Linux x86_64 + aarch64, macOS x86_64 + arm64, Windows amd64) +- Python 3.7 +- Python 3.8 +- Python 3.9 +- Python 3.10 +- Python 3.11 + +### Supported Platforms +- Linux (`manylinux`-compatible) x86_64 and aarch64 +- macOS Darwin x86_64 and arm64 +- Windows 64-bit + +## Usage +```python +from simplification.cutil import ( + simplify_coords, + simplify_coords_idx, + simplify_coords_vw, + simplify_coords_vw_idx, + simplify_coords_vwp, +) + +# Using Ramer–Douglas–Peucker +coords = [ + [0.0, 0.0], + [5.0, 4.0], + [11.0, 5.5], + [17.3, 3.2], + [27.8, 0.1] +] + +# For RDP, Try an epsilon of 1.0 to start with. Other sensible values include 0.01, 0.001 +simplified = simplify_coords(coords, 1.0) + +# simplified is [[0.0, 0.0], [5.0, 4.0], [11.0, 5.5], [27.8, 0.1]] + +# Using Visvalingam-Whyatt +# You can also pass numpy arrays, in which case you'll get numpy arrays back +import numpy as np +coords_vw = np.array([ + [5.0, 2.0], + [3.0, 8.0], + [6.0, 20.0], + [7.0, 25.0], + [10.0, 10.0] +]) +simplified_vw = simplify_coords_vw(coords_vw, 30.0) + +# simplified_vw is [[5.0, 2.0], [7.0, 25.0], [10.0, 10.0]] +``` + +Passing empty and/or 1-element lists will return them unaltered. + +## But I only want the simplified **Indices** +`simplification` now has: + +- `cutil.simplify_coords_idx` +- `cutil.simplify_coords_vw_idx` + +The values returned by these functions are the **retained** indices. In order to use them as e.g. a [masked array](https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html#what-is-a-masked-array) in Numpy, something like the following will work: + + import numpy as np + from simplification.cutil import simplify_coords_idx + + # assume an array of coordinates: orig + simplified = simplify_coords_idx(orig, 1.0) + # build new geometry using only retained coordinates + orig_simplified = orig[simplified] + + +## But I need to ensure that the resulting geometries are valid +You can use the topology-preserving variant of `VW` for this: `simplify_coords_vwp`. It's slower, but has a far greater likelihood of producing a valid geometry. + + +## But I Want to Simplify Polylines +No problem; [Decode them to LineStrings](https://github.com/urschrei/pypolyline) first. + +``` python +# pip install pypolyline before you do this +from pypolyline.cutil import decode_polyline +# an iterable of Google-encoded Polylines, so precision is 5. For OSRM &c., it's 6 +decoded = (decode_polyline(line, 5) for line in polylines) +simplified = [simplify_coords(line, 1.0) for line in decoded] +``` + +## How it Works +FFI and a [Rust binary](https://github.com/urschrei/rdp) + +## Is It Fast +I should think so. +### What does that mean +Using `numpy` arrays for input and output, the library can be reasonably expected to process around 2500 1000-point LineStrings per second on a Core i7 or equivalent, for a 98%+ reduction in size. +A larger LineString, containing 200k+ points can be reduced to around 3k points (98.5%+) in around 50ms using RDP. + +This is based on a test harness available [here](benchmark_runner.py). +#### Disclaimer +All benchmarks are subjective, and pathological input will greatly increase processing time. Error-checking is non-existent at this point. + +## License +[MIT](license.txt) + +## Citing `Simplification` +If Simplification has been significant in your research, and you would like to acknowledge the project in your academic publication, we suggest citing it as follows (example in APA style, 7th edition): + +> Hügel, S. (2021). Simplification (Version X.Y.Z) [Computer software]. https://doi.org/10.5281/zenodo.5774852 + +In Bibtex format: + + @software{Hugel_Simplification_2021, + author = {Hügel, Stephan}, + doi = {10.5281/zenodo.5774852}, + license = {MIT}, + month = {12}, + title = {{Simplification}}, + url = {https://github.com/urschrei/simplification}, + version = {X.Y.Z}, + year = {2021} + } + + +%prep +%autosetup -n simplification-0.6.7 + +%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-simplification -f filelist.lst +%dir %{python3_sitearch}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.7-1 +- Package Spec generated |