## Computing Square Corners

### 2021-02-25

How to compute square corner vertices? This post looks into two different approaches where the first method goes on to apply matrix multiplication within a algorithmic context that results in a C++ application. The second approach develops the idea of the first method by decomposing rotation matrix into its eigenvalue counterpart, which is then utilized in two different algorithms and in a second C++ program.

The question at hand can be formalized as follows.

Assume a square $$S$$ with a center point at origin of a coordinate system as is shown in Figure 1,

Square at its center point

and a requirement that states;

Requirement 1: Define algorithm for computing corner vertices $$P_n \in \mathbb{R}^2$$ of square $$S$$ having a center point at a given $$O$$, when $$n$$ is in the sequence $$\langle$$ 1 $$,$$ 2 $$,$$ 3 $$,$$ 4 $$\rangle$$.

The requirement can be satisfied as follows.

### Method 1: Applying the Rotation Matrix

Say that the side length of $$S$$ is $$2l$$. Then the first corner vertex, can be thought of as a vector

as is shown in the next figure.

Graph of the vector   $$P$$

Next coordinate, $$P$$, can then be derived from $$P$$ by multiplying it with the rotation matrix

angle of the two vertices $$P$$ and $$P$$ is $$\frac{\pi}{2}$$. In particular, $$P$$ $$=RP$$, as is shown below

Graph of transformation   $$RP$$

The statement $$P$$ $$=RP$$ can be generalized as $$P_n = RP_{n-1}$$ if positive integer $$n$$ is in the range $\begin{matrix} \left| \left(\pi - \frac{\pi}{4} \right)-\pi\right| \cdot \frac{4}{\pi} \ = \\[1em] 1 \ \leq \ n \ \leq \ 4 \\[1em] = \ \left| \left(\pi - \frac{4\pi}{4} \right)-\pi\right| \cdot \frac{4}{\pi}, \end{matrix}$ $$\theta$$ is as above, and the side length of the square is known.

Furthermore, equation $$P_n = RP_{n-1}$$ can now be expressed as

that fulfills Requirement 1.

The algorithm initializes with rotation matrix $$R$$, having the given right angle, and a array containing the first corner coordinate which can be determined from the argument $$S$$, as is shown at line $$1$$.

After this, a $$\text{\textbf{while}}$$-loop begins, that iterates from $3\frac{\pi}{4} \ \rightarrow \ 2\frac{\pi}{4} \ \rightarrow \ \frac{\pi}{4} \ \rightarrow \ 0. \tag{1}$ This means that the examined loop iterates three times and stops when there is no more $$\pi$$ left at the line $$2$$. That is, the outermost loop invariant reaches its termination condition when $$i \rightarrow 0$$ just after the first three values of sequence $$(1)$$. The values are then converted in to indexor value sequence $$\langle 1,2,3 \rangle$$ in the first index at line $$5$$, where these values designate any current index in $$A$$ where to place any coordinate $$P_n$$ of $$S$$ under iteration $$n$$.

Additionally, the $$A.$$Prev $$A[ \ \left( |i - \pi| \cdot \frac{4}{\pi} \right) - 1 \ ]$$. Or in other words, a member function of $$S$$ that returns $$P_{n-1}$$ in $$A$$.

Rest of the routine from lines $$3$$ to $$5$$ are for computing the matrix transform $$RP$$. When the loop terminates, solution array $$A$$ is returned with computed corner coordinates of $$S$$.

Is recommended to replace the lines $$\footnotesize 2$$ and $$\footnotesize 5$$ of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$ with lines

$$\quad \footnotesize \text{\scriptsize 2} \ \ \ \text{\textbf{for }} i = 1 \text{\textbf{ to }} A.\text{length} - 1 \text{\textbf{ do}}$$

and

$$\quad \footnotesize \text{\scriptsize 5} \ \quad \ \quad \ \quad \ A[i][k] \mathrel{+}= R[k][j] \cdot A[k-1][j]$$

in a production code in order to ease the readability and maintainability.

A possible implementation of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$ is given in the following

$$\text{\small\textbf{Source}}$$ $$\text{\small\textbf{Code}}$$ $$\text{\small\textbf{Listing}}$$ $$\text{\small\textbf{1}}$$

std::vector<Vertex> verticesOf(Square const& S)
{
using namespace std;
using namespace std::numbers;
using rotation_matrix = vector<vector<double>>;

double const theta = pi / 2;
double const l     = S.side_len * 0.5;
double i           = pi;

auto const n = [](double const& i) {
return static_cast <unsigned> (abs(i - pi) * (4 / pi));
};

rotation_matrix const R = {
{  cos(theta), sin(theta) },
{ -sin(theta), cos(theta) }
};

vector<Vertex> A = {
{l,l}, {0,0}, {0,0}, {0,0}
};

while (i -= pi / 4)
for (unsigned j = 0; j < A[0].size() - 1; j++)
for (unsigned k = 0; k < A[0].size() - 1; k++)
A[n(i)][j] += R[j][k] * A[n(i) - 1][k];

return A;
}

for some Vertex and Square. Notice that $$\text{\small \textbf{Source Code Listing 1}}$$ uses of the new <numbers> [See cppreference] header from the C++20 language standard (ISO/IEC, 2020) for the value of $$\pi$$.

Taking account of the recommendations from above, the line 24 could be written as

24 for (unsigned i = 0; i < A.size() - 1; i++)

and the line 27 as

27 A[i][j] += R[j][k] * A[i - 1][k];

Doing this allows discarding variable i and the lambda n of lines 9 and 11-13, and indeed eases the readability and maintainability by reducing the implementation into 25 LOC, if the $$\text{\textbf{\small Source Code Listing 1}}$$ is the chosen implementation of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$.

### Method 2: Applying the Rotation Matrix with a twist

The matrix multiplication $$RP_{n-1}$$ can be expressed differently.

If $P_n = R(\theta)P_{n-1} = \lambda P_{n-1}, \tag{2}$ for some $$\lambda$$, is multiplied by $$P_{n-1}^{-1}$$, then $R(\theta) = \lambda,$ and so $R(\theta) - \lambda = 0.$ Moreover, multiplying the rotation matrix $$R$$ and the proposed $$\lambda$$ with identity matrix $$\mathbf{I}$$ implies that $R(\theta) - \lambda\mathbf{I} = 0.$ Then the \begin{aligned} &\text{det}(R(\theta) - \lambda \mathbf{I}) \\[3pt] &= \text{det} \begin{bmatrix} \cos \theta - \lambda & - \sin \theta \\ \sin \theta & \sin \theta - \lambda \\ \end{bmatrix} \\[1em] &= (\cos \theta - \lambda)^2 + \sin^2 \theta \\[3pt] &= \theta^2 - 2 \lambda \cos \theta + 1 \\[3pt] &= 0, \end{aligned} where from it can be proven that \begin{aligned} \lambda &= \cos \theta \pm \sqrt{\cos^2 \theta - 1} \\ &= \cos \theta \pm \sin \theta i \\ &= \exp \pm \theta i, \end{aligned} as is shown by Haber (2019).

Hence, continuing with the $$\theta$$ of previous method, it follows from equation $$($$$$2$$$$)$$, that $P_n = \lambda P_{n-1} = \left( \exp \pm \frac{\pi}{4} i \right) P_{n-1}.$ Therefore it's possible to refactor the matrix multiplication logic of the $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$ by modifying it with the newfound information concerning the eigenvalue $$\lambda$$.

But before this can be done, few more insights are required.

First off, observe the following $$\mathbf{while}$$-loop of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$;

$$\footnotesize \quad {\scriptsize 2} \ \quad \text{\textbf{while}} \ (i = \frac{\pi}{4}) \leftarrow (\pi - i) \ \text{\textbf{do}}$$ $$(3)$$

where the indexor $$i$$ can now be thought of as being a complex number due to the observed imaginary term in $$\lambda$$. If the indexor is then initialized with $$-\sqrt{-1}$$ and iterated with multiplication by $$\sqrt{-1}$$ until $$i \rightarrow 1$$, the loop $$(3)$$ can be expressed as

$$\footnotesize \quad \text{\scriptsize 2}' \quad \text{\textbf{while}} \ (i = -\sqrt{-1}) \leftarrow (i \cdot \sqrt{-1}) \neq 1 \ \text{\textbf{do}}$$ $$(4)$$

or even

$$\footnotesize \quad \text{\scriptsize 2}' \quad \text{\textbf{while not}} \ (i = -\sqrt{-1}) \leftarrow (i \cdot \sqrt{-1}) \ \text{\textbf{do}}$$ $$(5)$$

where the iteration goes from

$i \ \rightarrow \ -1 \ \rightarrow \ -i \ \rightarrow \ 1, \tag{6}$

In addition, the given sequence can be used to drive the computation of corner coordinates of square $$S$$ as is shown in the second observation.

By inspecting the evaluation of the positive conjugate of $$\lambda$$, a constant $\exp \left( \frac{\pi\sqrt{-1}}{4}\right) = 0.7\ldots + 0.7\ldots i = c' \tag{7}$ is revealed, which can be multiplied by some complex number $$i$$ of the sequence $$(6)$$ generated in the pair of loops above, in order to derive a signed complex scalar constant $$c'i$$ for computing $$x$$ and $$y$$ values of a corner in $$S$$.

Each multiplication by $$c'i$$ results in a complex number that uncovers magnitudes of some coordinate in $$S$$, when the imaginary part in $$(7)$$ is ignored. However, the constants $$0.7\ldots$$ of $$c'$$ are necessary to be set to $$1$$ — this can be thought of as a squaring the circle step taken at design time — so that the product $$c'i$$ does not undershoot by a fraction of $$0.3\ldots$$ during the corner computations, as is demonstrated in the next figure

Squaring the circle step visualized

where the orange arrow indicates squaring of the circle for $$S$$. Therefore the revised multiplier constant simplifies to $c = 1 + i. \tag{8}$

Now, given the transformed $$\text{\textbf{while}}$$-loop $$(4)$$ or $$(5)$$, and the new multiplication constant $$(8)$$, the $$x$$ and $$y$$ components of a chosen corner coordinate $$P$$ of $$S$$ can be computed by including the following lines

\footnotesize \begin{aligned} \quad {\scriptsize 3}' \quad P.x \leftarrow l \cdot \operatorname{Re} \ ci\\ \quad {\scriptsize 4}' \quad P.y \leftarrow l \cdot \operatorname{Im} \ ci \end{aligned}

into the new reformumlation of the current algorithm under developmet, when $$l = S.\text{side\_len} \cdot \frac{1}{2}$$.

This is shown in the redesign of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{1}}$$ into

Suffice to say, this algorithm can be developed further.

If the scaling and assignment lines $$3$$ and $$4$$ are the done in-place of the Insert method call of $$A$$, the initialization of the vector $$P$$ at line $$1$$ becomes redundant, because the vector's purpose is simply to function as a temporary variable for holding data during the iteration of the algorithm.

Since it is good practice not to clutter code with unnecessary variables in general, $$P$$ should be refactored away with a more sufficient design, such as the instruction descriped;

$$\footnotesize \quad \text{\scriptsize 5}' \quad \ A.$$Insert$$\footnotesize ( \ l \cdot (\operatorname{Re} c, \operatorname{Im} c ) \ )$$

More over, it's evident that the $$\text{\textbf{while}}$$-loops $$(4-5)$$discussed earlier are or can be ambiguous, but fortunately an inquiry into them can open a possibility for a new formalization.

Main logic of the $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{2}}$$'s loop is to multiply $$c$$ with a updating $$i$$ that iterates trough its characteristic sequence $$(6)$$ in order to generate corner coordinatorial complex numbers where from to extract the coordinate information throughout the iteration. On the other hand, it is equally valid to update the value of $$c$$ and hold $$i$$ constant during the evaluation of $$ci$$.

When this idea is applied trough the usage of a $$\text{\textbf{for}}$$-loop construct, it is possible to evaluate $$ci$$ as

$$\footnotesize \quad {\scriptsize n} \ \ \textbf{for} \ c \leftarrow ci \ \textbf{to} \ \bar{c} \\$$

at some line $$n$$.

Depending on aesthetic inclinations, the line $$n$$ could also be expressed more compactly as

$$\footnotesize \quad {\scriptsize n} \ \ \textbf{for} \ c \mathrel{\cdot}= i \ \textbf{to} \ \bar{c}$$

where a the $$\mathrel{\cdot}=$$ operator from $$\mathbb{C} \times \mathbb{C} \rightarrow \mathbb{C}$$ can be thought of as having the meaning $\mathrel{\cdot}=(i, j) = (i \leftarrow i \cdot j).$

In any case, the variable $$c$$ is immediately multiplied with $$i$$ to get the first value of the product $$ci$$ where from to read the required information. Note that the iteration now just takes three steps, which is acceptable because array $$A$$ can be initialized with the first corner value $$(l,l)$$ since the $$l$$ is known at the beginning of $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{2}}$$.

This loop design of lines $$n$$ above reverts the loop logic such that the line $$5' = n + 1$$, so that the evaluation of $$S$$' corners happen a posteriori with respect to the main loop driving the computation — which is on contrary to the previous algorithm, where the evaluation is done a priori.

Putting together the ideas considered, a consequent algorithm can be structured;

that considerably clarifies the previous $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{2}}$$ and fulfills the Requirement 1.

Likewise this algorithm can be expressed in C++ as

$$\text{\small\textbf{Source}}$$ $$\text{\small\textbf{Code}}$$ $$\text{\small\textbf{Listing}}$$ $$\text{\small\textbf{2}}$$

auto verticesOf_(Square const& S)
{
std::complex<double> c {1.0, 1.0}, i {0.0, 1.0}, c_ = c;
double const l = S.side_len * 0.5;
auto A = std::make_unique <std::vector<Vertex>> (
std::initializer_list <Vertex> ({{l , l}})
);

for ( c *= i; c != c_; c *= i )
A->emplace_back( Vertex{ l * c.real(), l * c.imag() } );

return A.release();
}

### Conclusion

This essay began with a question on how to compute a corner vertices of a given square, and formalized it into a Requirement 1. From there on the problem was inspected on and two solutions were presented along with example C++ implementaitons.

Reasons for the study include, but are not limited to,

• study the problem in order to utilize possible new ideas in the future,
• interest for learning to develop software on a scientific basis,
• writing,
• develop the site,
• and learn and use common web-development tools.
Future post will present at least one more solution that simplifies $$\small \text{\textbf{Algorithm}}$$ $$\small \text{\textbf{3}}$$ further.

-Matti

### References:

Haber, H. (2019). Eigenvalues and eigenvectors of rotation matrices. [PDF]. Physics 116A. Retrieved: 17 February 2021, from http://scipp.ucsc.edu/~haber/ph116A/Rotation2.pdf

ISO/IEC. (2020). International Standard ISO/IEC 14882:2020(E) – Programming Language C++. Geneva, Switzerland: International Organization for Standardization (ISO). Retrieved: 23 February 2021, from https://isocpp.org/std/the-standard

Weisstein, E. W. (n.d.). Circle Squaring. Retrieved: 16 February 2021, from https://mathworld.wolfram.com/CircleSquaring.html