TinySpline

TinySpline is library for NURBS, B-Splines, and Bézier curves, allowing you to handle splines with ease. The library has been implemented in ANSI C (C89) and provides a wrapper for C++ (C++11) along with auto-generated bindings for C#, D, Java, Lua, Octave, PHP, Python, R, and Ruby. TinySpline strives to be very small by design with a minimum set of dependencies and an interface developed to be convenient without lacking enhanced features.

License

MIT License - see the LICENSE file in the source distribution.

Some Features of This Library

• Use a single struct for NURBS, B-Splines, Bézier curves, lines, and points.
• Support for opened and clamped splines.
• Create splines of any degree and dimension.
• Evaluate splines using De Boor's algorithm.
• Interpolate cubic splines using the Thomas algorithm.
• Insert knots and split splines without modifying the shape.
• Derive splines of any degree.
• Subdivide splines into Bézier curves.
• A wrapper for C++ (C++11) and bindings for C#, D, Java, Lua, PHP, Python, and Ruby.
• Easy to use with OpenGL.

Feel free to ask for more features via the issues or to contribute to TinySpline. :)

Getting Started

The following listing uses the C++ wrapper to give a short example of TinySpline:

#include <iostream>
#include "tinysplinecpp.h"

int main(int argc, char **argv)
{
	// Create a cubic spline with 7 control points in 2D using
	// a clamped knot vector. This call is equivalent to:
	// tinyspline::BSpline spline(7, 2, 3, TS_CLAMPED);
	tinyspline::BSpline spline(7);

	// Setup control points.
	std::vector<tinyspline::real> ctrlp = spline.ctrlp();
	ctrlp[0]  = -1.75f; // x0
	ctrlp[1]  = -1.0f;  // y0
	ctrlp[2]  = -1.5f;  // x1
	ctrlp[3]  = -0.5f;  // y1
	ctrlp[4]  = -1.5f;  // x2
	ctrlp[5]  =  0.0f;  // y2
	ctrlp[6]  = -1.25f; // x3
	ctrlp[7]  =  0.5f;  // y3
	ctrlp[8]  = -0.75f; // x4
	ctrlp[9]  =  0.75f; // y4
	ctrlp[10] =  0.0f;  // x5
	ctrlp[11] =  0.5f;  // y5
	ctrlp[12] =  0.5f;  // x6
	ctrlp[13] =  0.0f;  // y6
	spline.setCtrlp(ctrlp);

	// Stores our evaluation results.
	std::vector<tinyspline::real> result;

	// Evaluate `spline` at u = 0.4 using 'evaluate'.
	result = spline.evaluate(0.4f).result();
	std::cout << "x = " << result[0] << ", y = " << result[1] << std::endl;

	// Derive `spline` and subdivide it into a sequence of Bezier curves.
	tinyspline::BSpline beziers = spline.derive().toBeziers();

	// Evaluate `beziers` at u = 0.3 using '()' instead of 'evaluate'.
	result = beziers(0.3f).result();
	std::cout << "x = " << result[0] << ", y = " << result[1] << std::endl;

	return 0;
}

Installation

Compiling From Source

TinySpline uses the CMake build system to compile and package the interfaces. The C library has been implemented in C89 and, thus, should be compatible with every modern compiler. All other features of TinySpline are optional and will be disabled if CMake does not find the required dependencies; however, CMake and an appropriate C/C++ compiler must be available, regardless of the interface you want to build. TinySpline is tested using the following compiler suites: gcc, clang, and msvc. In order to compile the C++ wrapper or any of the bindings, your compiler suite (e.g. gcc) must support C++11. Additionally, Swig (in version 3.0.1 or above) is required to generate the bindings for other languages. Each binding may have further dependencies to generate the source code of the target language. The following table gives an overview:

Language	Dependencies to Generate Source	(Relative) Output Directory
C#		csharp
D	-	dlang
Golang	-	go
Java	Java Development Kit	org/tinyspline
Lua	Lua headers	lua
PHP	PHP (Zend) headers *	php
Python	Python headers	python
Ruby	Ruby headers	ruby

• Please note that macOS comes with PHP, but does not have the Zend headers. It is recommended to use a package manager (such as Homebrew) to obtain the headers.

To simplify the usage of the bindings, the generated source files will be compiled and/or packaged if necessary. That is, for instance, the generated Java files will be compiled to .class files and packaged into a single jar archive. Thus, the following tools are required if you want to package the corresponding binding:

Language	Required Tool(s)	Output File
C#	Any of: csc, mcs, dmcs, gmcs	TinySpline.dll
Java	javac and jar (available in JDK)	tinyspline.jar

The remaining bindings do not need to be packaged (usually the interpreted languages).

Now let's start building TinySpline. First of all, checkout the repository and cd into it:

git clone [email protected]:msteinbeck/tinyspline.git tinyspline
cd tinyspline

Afterwards, create a build directory and cd into it:

mkdir build
cd build

Finally, run CMake and build the libraries:

cmake ..
cmake --build .

You will find the resulting libraries, jars, etc. in tinyspline/build/lib.

Cross Compiling

In order to cross-compile the C and C++ library, use one of the provided toolchain files. Currently, toolchain files for MinGW, ARM, and AVR are available at the root directory of the source distribution (e.g. Toolchain-arm.cmake). Use the following command within your build directory to cross compile TinySpline to the desired platform:

cmake -DCMAKE_TOOLCHAIN_FILE=<path to tinyspline>/res/toolchain/Toolchain-*.cmake ..

Python 2 vs. Python 3

Swig needs to distinguish between Python 2 and Python 3 in order to generate source code that is compatible with the used environment. That is, Swig requires the parameter -py to generate Python 2 compatible code and -py3 to generate Python 3 compatible code. Thus, the CMake file used to compile and package the libraries configures Swig according to the version of the Python instance that was found during initialization. On systems with multiple versions of Python installed, CMake chooses the more recent one (i.e. Python 3). If you want to use a specific version of Python, set the environment variable 'TINYSPLINE_PYTHON_VERSION' to '2' or '3'.

The following example shows how to force CMake to use Python 2 rather than Python 3 on Debian-based systems:

export TINYSPLINE_PYTHON_VERSION=2
cmake ..

Disabling Bindings

For one reason or another, you may have the required packages to build a binding, but you don't want to compile it. You can pass an additional argument into CMake to prevent the specified language bindings from compiling:

cmake -DTINYSPLINE_DISABLE_CSHARP=YES ..

Install the C and C++ Libraries

The following command installs TinySpline to your system:

cmake --build . --target install

However, there are several binding-related files that CMake does not install with this command, as some languages use their own approach to install the files to your system. Python, for instance, uses Distutils/Setuptools to copy the resulting files to Python-specific installation directories that CMake is not aware of. Thus, TinySpline ships further, language-related distribution tools that will be explained in the following sections.

Install the Bindings

Depending on your configuration, binding-related distribution files are generated within the root of your build directory. That is, for instance, the file setup.py will be generated if support for Python has been detected. Currently, the following build tools are supported: Setuptools (Python), Maven (Java), and Luarocks (Lua).

Theoretical Backgrounds

[1] is a very good starting point for B-Splines.

[2] explains De Boor's Algorithm and gives some pseudo code.

[3] provides a good overview of NURBS with some mathematical background.

[4] is useful if you want to use NURBS in TinySpline.