Metadata-Version: 2.1
Name: mikutoolkit
Version: 0.0.7
Summary: A Simple Toolkit
Home-page: https://github.com/sandyzikun/mikutoolkit.git
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Description-Content-Type: text/markdown
License-File: LICENSE

# `mikutoolkit`

A Simple Toolkit.

![](https://github.com/sandyzikun/mikutoolkit/raw/init/fufu.gif)

> あなたもミクと創ろう、世界を繋ごう。 \
> Create your own Miku, which connects the World! \
> 創造屬於你的初音未來吧，連接起整個世界。 \
> ---- Livetune(kz) in "Tell Your World"

## Requirements

Ensure [NumPy](https://numpy.org/) ([`NumPy` on GitHub](https://github.com/numpy/numpy/)), and [Matplotlib](https://matplotlib.org/) ([`Matplotlib` on GitHub](https://github.com/matplotlib/matplotlib/)) is installed already before installing `mikutoolkit`.

One of most simple ways to install them is installing it with `conda`:

```sh
$ conda install numpy matplotlib
```

## Installation

Currently the latest version of `mikutoolkit` can be installed with `pip` as following:

```sh
$ pip install mikutoolkit --upgrade
```

or [from source](https://github.com/sandyzikun/mikutoolkit/) like other packages.

## Importation

To access `mikutoolkit` and its functions import it in your Python code like this:

```py
>>> import mikutoolkit as miku
あなたもミクと創ろう、世界を繋ごう。
```

## Changelog

### Version 0.0.6

* Added HMM (Hidden Markov Model) (`HMM_Traid`) and Fourier Series (`fourier.Series`), Dataset Class (`Linsep_Binary_Normal_Dataset`);

## References

## Extra

![](https://github.com/sandyzikun/mikutoolkit/raw/init/mikuv2.jpeg)

Hatsune Miku SAIKOU !!


