semvec/pypi-packages huggingface dataset:
pynetester 0.0.1
network tester for python
License: MIT

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                    pynetester
==================================================
            network tester for python

概述
====
pynetester模块是使用Python编写纠删码支持模块。

- 工程主页: https://github.com/zoumingzhe/pynetester
- 下载地址: https://pypi.python.org/pypi/pynetester
- 法律许可: MIT license_ , (C) 2021 ZouMingzhe_ <zoumingzhe@qq.com>

安装
====
通过pip命令安装pynetester模块：

``pip install pynetester``

如果已经安装pynetester模块，可以通过pip命令更新：

``pip install --upgrade pynetester``

更多安装信息请查阅 安装文档_ 。

文档
====
API（应用程序接口）文档、用法和例程可查阅 documentation_ 目录下的文档。

- .rst后缀文件可以在任何文本编辑器中查看或者使用 Sphinx_ 转换成HTML或PDF格式

例程
====
例程存放在工程文件的 examples_ 目录下。

测试
====
单元测试存放在工程文件的 test_ 目录下。

支持
====
本项目由 ZouMingzhe_ <zoumingzhe@qq.com> 创建并维护。

为了完善pynetester模块的功能，欢迎您贡献代码至: https://github.com/zoumingzhe/pynetester

语言
====
简体中文_

English_


.. _ZouMingzhe: https://zoumingzhe.github.io
.. _简体中文: https://github.com/zoumingzhe/pynetester/blob/master/README.rst
.. _English: https://github.com/zoumingzhe/pynetester/blob/master/documentation/en/README.rst
.. _license: https://github.com/zoumingzhe/pynetester/blob/master/LICENSE.txt
.. _安装文档: https://github.com/zoumingzhe/pynetester/tree/master/documentation/pynetester.rst#installation
.. _documentation: https://github.com/zoumingzhe/pynetester/tree/master/documentation
.. _examples: https://github.com/zoumingzhe/pynetester/tree/master/examples
.. _test: https://github.com/zoumingzhe/pynetester/tree/master/test
.. _Python: http://python.org/
.. _Sphinx: http://sphinx-doc.org/
humo 1.5.1.50
A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer
License: MIT

# humo
![Badge Status](https://ci-as-a-service)

A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer

## Description

A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer


***DEMO:***

## Features

- Intuitive operability
- Seamlessly from data shaping to analysis

For more information, see [humo -HP]().

## Requirement

- numpy
- scipy
- pandas
- matplotlib

## Usage

### quick start
```python
import humo

# loading data and making humo object
data = humo.dataIO.load_data() # open pkl file
cfg = humo.dataIO.load_cfg() # open cfg.json
obj = humo.motion.CoreMain(data, cfg) # make humo object

# get right shoulder angle
Rsho = obj.getJointAngle("Rshoulder")

# get multi data
shoulder = obj.getJointAngle(["Rshoulder","Lshoulder"])
shoulder.Lshoulder # getting Lshoulder angle
shoulder.Lshoulder.x # getting Lshoulder x axis angle
```

## Installation

 ```python
pip install humo
```

## Anything Else

The pickle data needed to create a humo object is created from a csv file.
By converting it to a pickle file, very fast data loading can be achieved.

```python
import humo

# Procedure to convert csv file to pkl file
c2p = humo.Preprocess.convert2pkl() # opening csv file
c2p.datacleansing() # cleansing csv data
c2p.convert2pkl() # save csv file as pkl file
```

## Author

[akira6](kobayashi.akira.5312@gmail.com)

## License

[MIT](http://b4b4r07.mit-license.org)