path: root/python-simplification.spec

%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
[![Build Status](https://github.com/urschrei/simplification/actions/workflows/wheels.yml/badge.svg)](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [![Coverage Status](https://coveralls.io/repos/github/urschrei/simplification/badge.svg?branch=master)](https://coveralls.io/github/urschrei/simplification?branch=master) [![Downloads](https://pepy.tech/badge/simplification)](https://pepy.tech/project/simplification)[![DOI](https://zenodo.org/badge/65199659.svg)](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

![Line](https://cdn.rawgit.com/urschrei/rdp/6c84264fd9cdc0b8fdf974fc98e51fea4834ed05/rdp.svg)  

## 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
[![Build Status](https://github.com/urschrei/simplification/actions/workflows/wheels.yml/badge.svg)](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [![Coverage Status](https://coveralls.io/repos/github/urschrei/simplification/badge.svg?branch=master)](https://coveralls.io/github/urschrei/simplification?branch=master) [![Downloads](https://pepy.tech/badge/simplification)](https://pepy.tech/project/simplification)[![DOI](https://zenodo.org/badge/65199659.svg)](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

![Line](https://cdn.rawgit.com/urschrei/rdp/6c84264fd9cdc0b8fdf974fc98e51fea4834ed05/rdp.svg)  

## 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
[![Build Status](https://github.com/urschrei/simplification/actions/workflows/wheels.yml/badge.svg)](https://github.com/urschrei/simplification/actions/workflows/wheels.yml) [![Coverage Status](https://coveralls.io/repos/github/urschrei/simplification/badge.svg?branch=master)](https://coveralls.io/github/urschrei/simplification?branch=master) [![Downloads](https://pepy.tech/badge/simplification)](https://pepy.tech/project/simplification)[![DOI](https://zenodo.org/badge/65199659.svg)](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

![Line](https://cdn.rawgit.com/urschrei/rdp/6c84264fd9cdc0b8fdf974fc98e51fea4834ed05/rdp.svg)  

## 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
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.7-1
- Package Spec generated