Showing posts with label B-spline. Show all posts
Showing posts with label B-spline. Show all posts

Sunday, July 11, 2021

Isogeometric Analysis: NURBS curves and surfaces in Octave and TypeScript

In this blog post I wrote some notes about B-splines. There are however important classes of curves and surfaces that cannot be represented by piecewise-polynomials like circles, ellipses etc... NURBS come to the rescue.

NURBS curves

NURBS is a generalization of B-splines where basis functions are defined with piecewise-rational polynomials. Again the parametric domain is split into multiple ranges by using a knot vector. The general definition is:

$$\boldsymbol{C}\left(\xi\right)=\sum_{i=0}^{n}R_{i}^{p}\left(\xi\right)\boldsymbol{P}_{i},\;a\leq\xi\leq b$$
$\boldsymbol{P}_{i}$ are the control points and the functions $R_{i}^{p}$ are the NURBS basis functions, defined as:

$$R_{i}^{p}\left(\xi\right)=\dfrac{N_{i}^{p}\left(\xi\right)w_{i}}{{\displaystyle\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}}},\;a\leq\xi\leq b,$$
where the functions $N_i^{p}$ are the B-spline basis functions (defined here):

$$N_{i}^{0}\left(\xi\right)=\left\{ \begin{array}{ll}1, & \xi_{i}\leq\xi<\xi_{i+1}\\0,&\text{otherwise}\end{array}\right.,a\leq\xi\leq b$$ $$N_{i}^{p}\left(\xi\right)=\frac{\xi-\xi_{i}}{\xi_{i+p}-\xi_{i}}\cdot N_{i}^{p-1}\left(\xi\right)+\frac{\xi_{i+p+1}-\xi}{\xi_{i+p+1}-\xi_{i+1}}\cdot N_{i+1}^{p-1}\left(\xi\right),a\leq\xi\leq b$$
and the values $w_i$'s are known as weights. The knot vector has the same definition given for B-spline curves:

$$\Xi=\left[\underset{p+1}{\underbrace{a,\ldots,a}},\xi_{p+1},\ldots\xi_{n},\underset{p+1}{\underbrace{b,\ldots,b}}\right],\;\left|\Xi\right|=n+p+2,$$

NURBS surfaces

By using the tensor product we can obtain definitions for NURBS in spaces of higher dimension. For surfaces, given the knot vectors:

$$\Xi=\left[\underset{p+1}{\underbrace{a_{0},\ldots,a_{0}}},\xi_{p+1},\ldots,\xi_{n},\underset{p+1}{\underbrace{b_{0},\ldots,b_{0}}}\right],\left|\Xi\right|=n+p+2$$ $$H=\left[\underset{q+1}{\underbrace{a_{1},\ldots,a_{1}}},\xi_{q+1},\ldots,\xi_{m},\underset{q+1}{\underbrace{b_{1},\ldots,b_{1}}}\right],\left|H\right|=m+q+2$$
a NURBS surface can be defined as:

$$\boldsymbol{S}\left(\xi,\eta\right)=\sum_{i=0}^{n}\sum_{j=0}^{m}R_{i,j}^{p,q}\left(\xi,\eta\right)\boldsymbol{P}_{i,j},\;\left\{ \begin{array}{c}a_{0}\leq\xi\leq b_{0}\\a_{1}\leq\eta\leq b_{1}\end{array}\right.$$
where:

$$R_{i,j}^{p,q}\left(\xi,\eta\right)=\dfrac{N_{i}^{p}\left(\xi\right)N_{j}^{q}\left(\eta\right)w_{i,j}}{{\displaystyle \sum_{\hat{i}=0}^{n}\sum_{\hat{j}=0}^{m}N_{\hat{i}}^{p}\left(\xi\right)N_{\hat{j}}^{q}\left(\eta\right)w_{\hat{i},\hat{j}}}},\;\left\{ \begin{array}{c}a_{0}\leq\xi\leq b_{0}\\a_{1}\leq\eta\leq b_{1}\end{array}\right.$$
and $w_{i,j}$ is the weight.

Homogeneous Coordinates

The implementations found in the repo do not directly implement the summations above, but use instead homogeneous coords to make calculations simpler. Let's consider the general form of a B-spline curve:

$$\boldsymbol{C}\left(\xi\right)=\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)\boldsymbol{P}_{i},\;a\leq\xi\leq b$$
Control points $\boldsymbol{P}_i$ can be written in homogeneous coords like this:

$$\boldsymbol{P}_{i}^{w}=\left[\begin{array}{c} x_{i}\\ y_{i}\\ z_{i}\\ 1 \end{array}\right]$$
We can multiply each control point by a value $w_i\neq 0$, and the result would still represent the same point in the euclidean space. As a result, we can write:

$$\boldsymbol{C}^{w}\left(\xi\right)=\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)\cdot\left[\begin{array}{c} x_{i}w_{i}\\ y_{i}w_{i}\\ z_{i}w_{i}\\ w_{i} \end{array}\right]=\left[\begin{array}{c} \sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)x_{i}w_{i}\\ \sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)y_{i}w_{i}\\ \sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)z_{i}w_{i}\\ \sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i} \end{array}\right]$$
$\boldsymbol{C}^w(\xi)$ is therefore the original B-spline curve in homogeneous coords. Now we can map back it to the euclidean space:

$$\boldsymbol{C}\left(\xi\right)=\left[\begin{array}{c} \frac{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)x_{i}w_{i}}{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}}\\ \frac{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)y_{i}w_{i}}{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}}\\ \frac{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)z_{i}w_{i}}{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}}\\ 1 \end{array}\right]$$
which yields:

$$\boldsymbol{C}\left(\xi\right)=\frac{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}\boldsymbol{P}_{i}}{\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)w_{i}}$$
This means that, moving to homogeneous coords, we can use a simpler form. Given:

$$\boldsymbol{P}_{i}^{w}=\left[\begin{array}{c} x_{i}w_{i}\\ y_{i}w_{i}\\ z_{i}w_{i}\\ w_{i} \end{array}\right]$$ we can write a NURBS curve as:

$$\boldsymbol{C}^{w}\left(\xi\right)=\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)\boldsymbol{P}_{i}^{w}$$
and a NURBS surface as:

$$\boldsymbol{S}^{w}\left(\xi,\eta\right)=\sum_{i=0}^{n}\sum_{j=0}^{m}N_{i}^{p}\left(\xi\right)N_{j}^{q}\left(\eta\right)\boldsymbol{P}_{i}^{w}$$
All the implementations in the repo use these simpler forms.

Octave Implementation

The computeNURBSBasisFun script can be used to compute NURBS basis functions. The drawNURBSBasisFunsP5 draws:

in the plots the effect of the weight is pretty clear. From top to bottom, the degree of the basis funs is increased over the knot vector $ Xi = [0.25, 0.5, 0.75]$.
The computeNURBSCurvePoint script uses homogeneous coords to compute a NURBS curve using B-spline basis functions. We can build curves similar to what we could draw with B-splines but we can also draw circles:

This is an example that shows what happens when a weight is increased on one point:

For NURBS surfaces instead we can draw bivariate basis functions. In these two examples, the first shows what happens when weights are all equal to 1, the second when weights are not all equal:



Now with the computeNURBSSurfPoint, using homogeneous coords, we can draw some interesting surfaces. Scripts are included to draw a plate with a hole:
and one is provided to draw a toroid:

TypeScript Implementation

The same implementation is provided for TypeScript, so you can experiment with the browser. With the NurbsCurve you can compute NURBS basis functions:

Saturday, June 26, 2021

Isogeometric Analysis: B-spline Curves and Surfaces in Octave and TypeScript

In the previous blog post here I implemented Bézier curves. There are other important structures that are used in computer graphics and I'd need those structures to define a domain and a solution in IGA for my implementation here: https://github.com/carlonluca/isogeometric-analysis.

Bézier curves are great, but the polynomials needed to describe some curves may need a high degree to satisfy multiple constraints. To overcome this problem, some structures were designed to use piecewise-polynomials instead. Examples in this case are NURBS and B-splines.

B-spline Curves

B-splines are curves that are described using piecewise-polynomials with minimal support. The parametric domain is split into multiple ranges by using a vector. The general definition of a B-spline curve is:

$$\boldsymbol{C}\left(\xi\right)=\sum_{i=0}^{n}N_{i}^{p}\left(\xi\right)\boldsymbol{P}_{i},\;a\leq\xi\leq b$$
where $\boldsymbol{P}_{i}$'s are the control points of the curve and the functions $N_{i}^{p}\left(\xi\right)$ are basis functions defined as:

$$N_{i}^{0}\left(\xi\right)=\left\{ \begin{array}{ll}1, & \xi_{i}\leq\xi<\xi_{i+1}\\0,&\text{otherwise}\end{array}\right.,a\leq\xi\leq b$$ $$N_{i}^{p}\left(\xi\right)=\frac{\xi-\xi_{i}}{\xi_{i+p}-\xi_{i}}\cdot N_{i}^{p-1}\left(\xi\right)+\frac{\xi_{i+p+1}-\xi}{\xi_{i+p+1}-\xi_{i+1}}\cdot N_{i+1}^{p-1}\left(\xi\right),a\leq\xi\leq b$$
The values $\xi_{i}$ are elements of the aforementioned knot vector, defined as:

$$\Xi=\left[\underset{p+1}{\underbrace{a,\ldots,a}},\xi_{p+1},\ldots,\xi_{n},\underset{p+1}{\underbrace{b,\ldots,b}}\right],\left|\Xi\right|=n+p+2$$
where $p$ is the degree of the basis functions. A knot vector in this form is said to be nonperiodic or clamped or open.

B-spline Surfaces

By using the tensor product we can obtain B-splines in spaces of higher dimension. For surfaces, given the knot vectors:

$$\Xi=\left[\underset{p+1}{\underbrace{a_{0},\ldots,a_{0}}},\xi_{p+1},\ldots,\xi_{n},\underset{p+1}{\underbrace{b_{0},\ldots,b_{0}}}\right],\left|\Xi\right|=n+p+2$$ $$H=\left[\underset{q+1}{\underbrace{a_{1},\ldots,a_{1}}},\xi_{q+1},\ldots,\xi_{m},\underset{q+1}{\underbrace{b_{1},\ldots,b_{1}}}\right],\left|H\right|=m+q+2$$
a B-spline surface can be defined as:

$$\boldsymbol{S}\left(\xi,\eta\right)=\sum_{i=0}^{n}\sum_{j=0}^{m}N_{i}^{p}\left(\xi\right)N_{j}^{q}\left(\eta\right)\boldsymbol{P}_{i,j},\;\left\{ \begin{array}{c} a_{0}\leq\xi\leq b_{0}\\ a_{1}\leq\eta\leq b_{1} \end{array}\right.$$
where $p$ and $q$ are the degrees of the polynomials. In the implementations, sometimes I preferred the matrix form of the equations:

$$\boldsymbol{C}\left(\xi\right)=\left[N_{i-p}\left(\xi\right),\ldots,N_{i}\left(\xi\right)\right]\cdot\left[\begin{array}{c} \boldsymbol{P}_{i-p}\\ \vdots\\ \boldsymbol{P}_{i} \end{array}\right],\;\xi\in\left[\xi_{i},\xi_{i+1}\right)$$
For the surfaces instead, the matrix form is: $$\boldsymbol{S}\left(\xi,\eta\right)=\left[N_{i-p}\left(\xi\right),\ldots,N_{i}\left(\xi\right)\right]\cdot\left[\begin{array}{ccc} \boldsymbol{P}_{j-q,i-p} & \cdots & \boldsymbol{P}_{j-q,i}\\ \vdots & \ddots & \vdots\\ \boldsymbol{P}_{j,i-p} & \cdots & \boldsymbol{P}_{j,i} \end{array}\right]\cdot\left[\begin{array}{c} N_{j-q}\left(\eta\right)\\ \vdots\\ N_{j}\left(\eta\right) \end{array}\right],$$ $$\xi\in\left[\xi_{i},\xi_{i+1}\right),\eta\in\left[\eta_{j},\eta_{j+1}\right)$$
These forms leverage a more performant algorithm for the computation of the basis functions, which returns the value of all nonvanishing functions for a point in the parametric space. The Octave implementation is clearly simpler as Octave has native support for matrices, the TypeScript implementation instead includes a basic Matrix2 class that offers the simplest operators.

Octave Implementation

An implementation for Octave is provided in https://github.com/carlonluca/isogeometric-analysis/tree/master/3.4. There are examples to show how to draw B-spline curves with the implementation.
For example, the drawBsplineBasisFuns script shows the B-spline basis functions over the knot vector $\Xi=[0, 0, 0, 1, 2, 3, 4, 4, 5, 5, 5]$ using the provided implementation of the basis functions:



The drawBsplineCurve script draws, instead, the real curve. For example, to draw the B-spline of degree $p=2$ defined over the knot vector $\Xi=[0, 0, 0, 0.25, 0.5, 0.75, 1, 1, 1]$ with control points:

$$\boldsymbol{P}_{0}=\left(0,0,0\right),\;\boldsymbol{P}_{1}=\left(1,1,1\right),\;\boldsymbol{P}_{2}=\left(2,0.5,0\right)$$ $$\boldsymbol{P}_{3}=\left(3,0.5,0\right),\;\boldsymbol{P}_{4}=\left(0.5,1.5,0\right),\;\boldsymbol{P}_{5}=\left(1.5,0,1\right)$$

a simple call to:

drawBsplineCurve(5, 2, [
    0, 0, 0, 0.25, 0.5, 0.75, 1, 1, 1
], [
    0, 0; 1, 1; 2, 0.5; 3, 0.5; 0.5, 1.5; 1.5, 0
]);


draws:



For surfaces, drawBivariateBsplineBasisFuns can be used to draw bivariate basis functions. For example:

drawBivariateBsplineBasisFuns([
    0, 0, 0, 0.5, 1, 1, 1
], 3, 2, [
    0, 0, 0, 0.5, 1, 1, 1
], 3, 2);


gives this result:

By using the defined basis functions, data defined in https://github.com/carlonluca/isogeometric-analysis/blob/master/3.4/defineBsplineRing.m can draw a shape similar to a ring:



Note that this is not yet a toroid.

TypeScript Implementation

A TypeScript implementation is also present in the repo. With a simple code like this: