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https://github.com/rafsaf/tw-complex

Algorithms for TW
https://github.com/rafsaf/tw-complex

mit numpy poetry pypi-package python scipy sklearn

Last synced: 14 days ago
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Algorithms for TW

Host: GitHub
URL: https://github.com/rafsaf/tw-complex
Owner: rafsaf
License: mit
Created: 2021-05-10T22:48:51.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2022-10-26T18:50:34.000Z (about 2 years ago)
Last Synced: 2024-10-11T08:21:08.516Z (about 1 month ago)
Topics: mit, numpy, poetry, pypi-package, python, scipy, sklearn
Language: Python
Homepage: https://pypi.org/project/tw-complex/
Size: 3.4 MB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

        ![GitHub](https://img.shields.io/github/license/rafsaf/tw-complex)

![PyPI](https://img.shields.io/pypi/v/tw-complex)

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/tw-complex)

# TW Complex

Repo with algorithms to divide ally villages into front and back in TW.

Underneath it is a problem of dividing a set of 2D points **A** according to the `min_radius` and `max_radius` distances from a set of other 2D points **B**, which can be solved most simply by counting the distances from each point in the first set **A** to all points in the second set **B** one by one.

- [Instalation](#instalation)

- [Basic usage](#basic-usage)

- [Examples](#examples-before---after)

- [Running locally](#running-locally)

# Instalation

```bash

pip install tw_complex

```

# Basic usage

```python

from tw_complex import CDistBrute

import numpy as np

# The code for Example 1 below

points1 = np.random.rand(10000, 2) + [2, 0]

points2 = np.random.rand(15000, 2)

min_radius = 1.4

max_radius = 2

precise_front, precise_back = CDistBrute(

    ally_villages=points1,

    enemy_villages=points2,

    min_radius=min_radius,

    max_radius=max_radius,

).result()

```

# Examples (before -> after)

### Example 1

```bash

Ally: 10000 points

Enemy: 15000 points

min_radius: 1.4

max_radius: 2

```

![example1](https://raw.githubusercontent.com/rafsaf/tw-complex/main/images/Figure_1.png)

### Example 2

```bash

Ally: 2500 points

Enemy: 6000 points

min_radius: 4

max_radius: 10

```

![example2](https://raw.githubusercontent.com/rafsaf/tw-complex/main/images/Figure_2.png)

### Example 3

```bash

Ally: 20000 points

Enemy: 20000 points

min_radius: 20

max_radius: 60

```

![example3](https://raw.githubusercontent.com/rafsaf/tw-complex/main/images/Figure_3.png)

### Example 4

```bash

Ally: 20000 points

Enemy: 20000 points

min_radius: 10

max_radius: 120

```

![example4](https://raw.githubusercontent.com/rafsaf/tw-complex/main/images/Figure_4.png)

# Running locally

You will need to have [poetry](https://python-poetry.org/) installed.

```

git clone https://github.com/rafsaf/tw-complex.git

cd tw-complex

poetry install

```

Code lives in `tw-complex` folder, and you may also test algorithms running in main folder

```

# In main folder

# eg. ~/Desktop/tw-complex

pytest

```

For CDistAndKNN it looks like

```python

# tests/test_cdist.py

from tw_complex import CDistAndKNN

import tests.utils as utils

def test_CDistAndKNN():

    utils.run_all_tests(CDistAndKNN, "CDistAndKNN", _precision=0.8, draw=True)

# Go with `draw=False` if you do not want to use pyplot to show diagrams

```

Some hardcoded tests are located in `tests/utils.py`, it uses brute force for calculating exact result, then compare it to given algorithm using basic maths. You can even compare it to brute force itself (eg. using diffrent `_precision`). For new test there should be another file in `tests/test_name_of_file_in_tw_complex_folder.py` with pretty much the same content as above.