semvec/pypi-packages huggingface dataset:
VirxERLU-CLib 2.0.9
C modules for VirxERLU
License: MIT
Requires Python: >=3.7

# VirxERLU

Big thanks to ddthj/GoslingUtils for the basis of VirxERLU. However, VirxERLU improves upon many things. This includes pathfinding, shot validation, and aerials. It also adds many things, like support for TMCP and a GUI for debugging. This also improves on the general performance of the agent.

+ [RLBot](http://www.rlbot.org/)
+ [VirxERLU Wiki](https://github.com/VirxEC/VirxERLU/wiki)
+ [VirxEC Discord](https://discord.gg/5ARzYRD2Na) - Ask your questions here!
+ [RLBot Wiki](https://github.com/RLBot/RLBot/wiki)
+ [RLBot Discord](https://discord.gg/rlbot)
+ [RLBot Youtube](https://www.youtube.com/channel/UCu8scB_k94Kh-iO979QTDJA)
+ [VirxEC Showcase](https://www.virxcase.dev)
+ [VirxERLU on VirxEC Showcase](https://virxerlu.virxcase.dev/)
+ [VirxEB on VirxEC Showcase](https://virxeb.virxcase.dev/)

## About

+ [Main GitHub page](https://github.com/VirxEC/VirxERLU)
+ [Cloning to another repository](https://github.com/VirxEC/VirxERLU/generate)
+ [Get the zip](https://github.com/VirxEC/VirxERLU/archive/master.zip)

VirxERLU is a series of utilities for RLBot.
All code in this repositry is in the public domain, so you can edit and distribute the code however you want to.

I made VirxERLU because it forces me to keep innovating on my bot in order to stay ahead of the curve. Any code in my bot [VirxEB](https://github.com/VirxEC/VirxEB) is NOT in the public domain.

VirxERLU will be updated after every tournament with the latest, *stable* features of VirxEB.

## Wiki

The wiki is the best way to get general information about VirxERLU.

+ [github.com/VirxEC/VirxERLU/wiki](https://github.com/VirxEC/VirxERLU/wiki)

## Tutorials

If you're going to use VirxERLU, be sure to watch the GoslingUtils tutorial first. The VirxERLU tutorial is only for the differences between the utils.

+ RLBot/GoslingUtils tutorial: [youtube.com/watch?v=lPkID_IH88U](https://www.youtube.com/watch?v=lPkID_IH88U)
+ VirxERLU tutorials: [youtube.com/playlist?list=PLeo0zkmzSE-UUFV-bd2vWtqiqe2cjaQNf](https://www.youtube.com/playlist?list=PLeo0zkmzSE-UUFV-bd2vWtqiqe2cjaQNf)
clusterzeug 0.10
Some functions for clustering
License: MIT
Keywords: clustering,data


# Some functions for clustering 

## Tested against Windows / Python 3.11 / Anaconda

## pip install clusterzeug

```python


from clusterzeug import (
    birchcluster,
    gaussianmixture,
    opticscluster,
    hdbscancluster,
    dbscan,
    agglomerativeclustering,
    spectralclustering,
    kmeanscluster,
    minibatchkmeanscluster,
    afinity_propagation,
    mean_shift,
)
import numpy as np
import random
data = np.array(
    [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(100)],
    dtype=np.int64,
)
a1 = birchcluster(data, n_clusters=10)
a2 = gaussianmixture(data, n_components=5)
a3 = opticscluster(data, min_samples=5)
a4 = hdbscancluster(data, min_cluster_size=5)
a5 = dbscan(data, eps=0.5, min_samples=5)
a6 = agglomerativeclustering(data, n_clusters=10)
a7 = spectralclustering(data, n_clusters=10)
res = kmeanscluster(data, n_clusters=10)
print(res)
res2 = minibatchkmeanscluster(data, n_clusters=10)
print(res2)
aff = afinity_propagation(data, damping=0.5, preference=-10)
print(aff)
ms = mean_shift(data,bandwidth=2.0)
print(ms)

```
biogemeUtilities 1.0.1
Add features to the biogeme package
License: MIT
Requires Python: >=3.8.18
Keywords: biogeme,discrete choice models,confidence interval,calibrate

The `biogemeUtilities` is intended to add some quality-of-life features to the biogeme package. 
It inherit the features from biogeme, while adding some new functionality. 
The simplest way to use it, is to create a biogemeObject using the biogemeUtilities package, 
but it can also be used in existing script using biogemeObjects created directly in the biogeme package.
Examples of how to use this package are included below the relevant functions.

The full credit for the awesome biogeme package goes to Prof. Michel Bierlaire. 
Please visit the biogeme website for at full documentation of biogeme: https://biogeme.epfl.ch/

Version 1.0.0b1
2023-10-28
- First (beta) release on PyPI
- Compatible with biogeme 3.2.12