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https://github.com/msteinbeck/tinyspline
ANSI C library for NURBS, B-Splines, and Bézier curves with interfaces for C++, C#, D, Go, Java, Javascript, Lua, Octave, PHP, Python, R, and Ruby.
https://github.com/msteinbeck/tinyspline
b-splines bezier-curves nurbs splines
Last synced: 4 days ago
JSON representation
ANSI C library for NURBS, B-Splines, and Bézier curves with interfaces for C++, C#, D, Go, Java, Javascript, Lua, Octave, PHP, Python, R, and Ruby.
- Host: GitHub
- URL: https://github.com/msteinbeck/tinyspline
- Owner: msteinbeck
- License: mit
- Created: 2014-09-25T20:13:48.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2024-09-03T22:18:21.000Z (4 months ago)
- Last Synced: 2024-12-10T16:00:51.322Z (11 days ago)
- Topics: b-splines, bezier-curves, nurbs, splines
- Language: C
- Homepage:
- Size: 4.32 MB
- Stars: 1,216
- Watchers: 64
- Forks: 209
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
- awesome-robotic-tooling - tinyspline - TinySpline is a small, yet powerful library for interpolating, transforming, and querying arbitrary NURBS, B-Splines, and Bézier curves. (Planning and Control / Vector Map)
README
TinySpline
========
TinySpline is a small, yet powerful library for interpolating, transforming,
and querying arbitrary NURBS, B-Splines, and Bézier curves. The core of the
library is written in ANSI C (C89) with a C++ wrapper for an object-oriented
programming model. Based on the C++ wrapper, auto-generated bindings for C#, D,
Go, Java, Javascript, Lua, Octave, PHP, Python, R, and Ruby are provided.
### Table of Contents
- [License](#license)
- [Features](#features)
- [Installation](#installation)
* [Pre-built Binaries](#pre-built-binaries)
* [Compiling From Source](#compiling-from-source)
- [Getting Started](#getting-started)
- [Documentation](#documentation)
- [Publications](#publications)
- [Theoretical Backgrounds](#theoretical-backgrounds)
### License
MIT License - see the LICENSE file in the source distribution.
### Features
- Object-oriented programming model
- B-Splines of any degree and dimensionality
- Spline interpolation
- Cubic natural
- Centripetal Catmull–Rom
- Evaluation
- Knots
- Sampling (multiple knots at once)
- Equidistant points
- Components (find y for given x)
- Reparametrization by arc length
- Mapping length <--> knot
- Knot insertion (refinement)
- Sub-spline extraction
- Bézier curve decomposition
- (also known as subdivision)
- Derivative
- Degree elevation
- Computation of rotation minimizing frames
- Morphing
- Serialization (JSON)
- Vector math
### Installation
#### Pre-built Binaries
Releases can be downloaded from the
[releases](https://github.com/msteinbeck/tinyspline/releases) page. In
addition, the following package manager are supported:
Conan (C/C++):
https://conan.io/center/tinyspline
NuGet (C#):
```xml
```
Go:
```bash
go get github.com/tinyspline/[email protected]
```
Luarocks (Lua):
```bash
luarocks install --server=https://tinyspline.github.io/lua tinyspline
```
Maven (Java):
```xml
org.tinyspline
tinyspline
0.6.0-1
```
PyPI (Python):
```bash
python -m pip install tinyspline
```
RubyGems (Ruby):
```bash
gem install tinyspline
```
#### Compiling From Source
See [BUILD.md](BUILD.md).
### Getting Started
A variety of examples (tests) can be found in the [test](test)
subdirectory.
The following listing shows a Python example:
```python
from tinyspline import *
import matplotlib.pyplot as plt
spline = BSpline.interpolate_cubic_natural(
[
100, -100, # P1
-100, 200, # P2
100, 400, # P3
400, 300, # P4
700, 500 # P5
], 2) # <- dimensionality of the points
# Draw spline as polyline.
points = spline.sample(100)
x = points[0::2]
y = points[1::2]
plt.plot(x, y)
# Draw point at knot 0.3.
vec2 = spline.eval(0.3).result_vec2()
plt.plot(vec2.x, vec2.y, 'ro')
# Draw tangent at knot 0.7.
pos = spline(0.7).result_vec2() # operator () -> eval
der = spline.derive()(0.7).result_vec2().normalize() * 200
s = pos - der
t = pos + der
plt.plot([s.x, t.x], [s.y, t.y])
# Draw 15 normals with equidistant distribution.
knots = spline.equidistant_knot_seq(15)
frames = spline.compute_rmf(knots)
for i in range(frames.size()):
pos = frames.at(i).position
nor = pos + frames.at(i).normal * 20
# You can also fetch the tangent and binormal:
# frames.at(i).tangent
# frames.at(i).binormal
plt.plot([pos.x, nor.x], [pos.y, nor.y], 'g')
plt.show()
```
Result:
### Documentation
The latest Doxygen documentation can be found at:
https://msteinbeck.github.io/tinyspline/
The documentation of the C interface
(https://msteinbeck.github.io/tinyspline/tinyspline_8h.html) is quite
extensive and also serves as an entry point for the C++ interface
documentation (as well as the documentation for the bindings created
from the C++ interface).
### Publications
If you use TinySpline in your research, please cite it as below.
```
@INPROCEEDINGS{Steinbeck:SANER:21,
author = {Steinbeck, Marcel and Koschke, Rainer},
booktitle = {2021 IEEE International Conference on Software
Analysis, Evolution and Reengineering (SANER)},
title = {TinySpline: A Small, yet Powerful Library for
Interpolating, Transforming, and Querying NURBS,
B-Splines, and Bézier Curves},
year = {2021},
pages = {572-576},
doi = {10.1109/SANER50967.2021.00068}
}
```
Other publications:
```
@INPROCEEDINGS{Steinbeck:VISSOFT:22,
author = {Steinbeck, Marcel and Koschke, Rainer},
booktitle = {2022 Working Conference on Software Visualization
(VISSOFT)},
title = {Edge Animation in Software Visualization},
year = {2022},
pages = {63-74},
doi = {10.1109/VISSOFT55257.2022.00015}
}
```
### Theoretical Backgrounds
[[1]](http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/B-spline/bspline-curve.html)
is a very good starting point for B-Splines.
[[2]](http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/B-spline/de-Boor.html)
explains De Boor's Algorithm and gives some pseudo code.
[[3]](http://www.codeproject.com/Articles/996281/NURBS-curve-made-easy)
provides a good overview of NURBS with some mathematical background.
[[4]](http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/NURBS/NURBS-def.html)
is useful if you want to use NURBS in TinySpline.