Metadata-Version: 2.1
Name: pyarcknot
Version: 0.0.2
Summary: A package for studying the arc diagrams of mathematical knots
Home-page: https://github.com/inigorrix/pyarcknot
Author: inigorrix
Author-email: inigorrix@gmail.com
License: MIT
Keywords: knot,knot diagram,arc diagram,jones polynomial,turaev surface
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: matplotlib
Requires-Dist: numba
Requires-Dist: numpy
Requires-Dist: sympy

PyArcKnot
===

PyArcKnot is a package for studying the arc diagrams of mathematical knots.

It was developed as part of my Final Project for my Industrial Design Engineering Degree, with the help and support of Pedro González Manchón.
The Final Project paper (in Spanish) can be found [here](https://oa.upm.es/77063/).


The following is just a showcase of some of the most important functions.
For a more in-depth demonstration of the possibilities available, check out the [Jupyter Notebook demo](https://github.com/inigorrix/pyarcknot_demo/blob/main/pyarcknot_demo.ipynb).

The package requires [NumPy](https://numpy.org/), [Matplotlib](https://matplotlib.org/), [Sympy](https://www.sympy.org/) and [Numba](https://numba.pydata.org/). They can be installed by running:

```bash
pip install numpy matplotlib sympy numba
```

To install the PyArcKnot package run:

```bash
pip install pyarcknot
```

The package consists of 4 modules:

```python
import pyarcknot.knot_matrix as km
import pyarcknot.knot_diagram as kd
import pyarcknot.knot_calculate as kc
import pyarcknot.turaev_surface as ts
```

### Knot Matrix

Knot Matrix is used to define the knot diagrams as [NumPy](https://numpy.org/) arrays in order to be able to work with them

```python
k8_21_arc = km.clean_k_arc('2 7 1 4 3 5 4 8 2 6 1 5 3 7 6 8')
k8_21_xco = km.xco_arc(k8_21_arc)
print(k8_21_xco)
```
	[[0 0 0 0 0 1 0 2]
	 [0 0 1 0 0 3 2 0]
	 [1 0 3 0 2 0 0 0]
	 [0 1 3 0 3 2 0 0]
	 [0 0 0 2 3 0 3 1]
	 [0 0 2 3 1 0 0 0]
	 [2 3 0 1 0 0 0 0]
	 [0 2 0 0 0 0 1 0]]


### Knot Diagram

Knot Diagram uses [Matplotlib](https://matplotlib.org/) to display diagrams of the knot.

```python
kd.draw_arc(k8_21_xco)
```

![arc_diagram](https://github.com/inigorrix/pyarcknot/blob/main/docs/arc_diagram.png?raw=true)


It can also return the number of loops in a smoothed diagram

```python
kd.draw_diagrams(k8_21_xco)
```

Number of crossings = 8

![arc_diagram](https://github.com/inigorrix/pyarcknot/blob/main/docs/smooth_a.png?raw=true)

|s_A D| = 5 

![arc_diagram](https://github.com/inigorrix/pyarcknot/blob/main/docs/arc_diagram.png?raw=true)

![arc_diagram](https://github.com/inigorrix/pyarcknot/blob/main/docs/smooth_b.png?raw=true)

|s_B D| = 1 


### Knot Calculate

Knot Calculate is used to calculate properties of the diagram such as the Kauffman Bracket Polynomial or the Jones Polynomial.
For this, [Sympy](https://www.sympy.org/) was used to work with polynomials and [Numba](https://numba.pydata.org/) to increase the performance and reduce the calculation time.

```python
kc.kauffman_bracket(k8_21_xco)
```

$\displaystyle A^{16} - 2 A^{12} + 2 A^{8} - 3 A^{4} + 3 - \frac{2}{A^{4}} + \frac{2}{A^{8}}$

```python
kc.jones_polynomial(k8_21_xco)
```

$\displaystyle \frac{2}{t} - \frac{2}{t^{2}} + \frac{3}{t^{3}} - \frac{3}{t^{4}} + \frac{2}{t^{5}} - \frac{2}{t^{6}} + \frac{1}{t^{7}}$


### Turaev Surface

Turaev Surface uses [Matplotlib](https://matplotlib.org/) to render a 3D surface obtained from the diagram of the knot.

```python
ts.turaev_surf(k8_21_xco)
```

![arc_diagram](https://github.com/inigorrix/pyarcknot/blob/main/docs/turaev_surface.png?raw=true)
