semvec/pypi-packages huggingface dataset:
huishi 1.0.0
A package that can let you create a poem by AI

# 绘诗诗词自动生成系统

## 简介
这里是绘诗诗词自动生成系统所提供的python库。您可以借用此库里面的如下函数，完成我们提供的诗词自动生成demo

首先，您可以使用以下命令，在您的计算机中使用pip安装我们所提供的基于绘诗诗词自动生成系统设计的python库。
    
    pip install huishi

如果您想要了解代码中模型的运行原理，或者希望借用我们的预训练模型训练自己的NLP模型，可以参考我们的[Github仓库](https://github.com/123xnc/keywords_to_poem)或者[gitee仓库](https://gitee.com/wangshixincheng/keywords_to_poem)

在这个python库中，我们为您提供了以下API：

    key_to_poem_V(keywords) ;关键词到五言诗
    key_to_poem_VII(keywords);关键词到七言诗
    seq_to_poem_V(keywords); 描述语句到五言诗
    seq_to_poem_VII(keywords);描述语句到七言诗
其分别代表输入关键字或者一段对诗句的描述语言，利用模型自动输出五言或者七言诗句作为返回值。输入参数和返回值都是序列类型。

如果在使用中有任何问题，可以通过我们的[邮箱](2020302111360@whu.edu.cn)或者直接在项目负责人中联系我们，我们会给予力所能及的最大帮助。如果觉得我们的项目对您有帮助的话，请麻烦去我们的[项目](https://github.com/123xnc/keywords_to_poem)中为我们点个⭐，谢谢了！
forkofthemotulator 0.0.5
A package for the motulator fork
Requires Python: >=3.6

# *motulator:* Motor Drive Simulator in Python

Introduction
------------
This open-source software includes simulation models for an induction motor, a synchronous reluctance motor, and a permanent-magnet synchronous motor. The motor models are simulated in the continuous-time domain while the control algorithms run in discrete time. The default solver is the explicit Runge-Kutta method of order 5(4) from scipy.integrate.solve_ivp. Simple control algorithms are provided as examples. 

<img src="pwm.png" alt="PWM waveforms" width="320"/><img src="pmsm.png" alt="Speed and torque waveforms" width="320"/>

Installation
------------
This software can be installed using pip: 

```bash
pip install motulator
```
Alternatively, the repository can be cloned. Running `__init__.py` in the folder `motulator` allows importing the package.

Usage
-----
The following example shows how to create a continuous-time system model, a discrete-time controller, and a simulation object:
```python3
import motulator as mt

# Continuous-time model for the drive system
motor = mt.InductionMotor()     # Motor model
mech = mt.Mechanics()           # Mechanics model
conv = mt.Inverter() 	        # Converter model
mdl = mt.InductionMotorDrive(motor, mech, conv)

# Discrete-time controller 
pars = mt.InductionMotorVectorCtrlPars() 	# Dataclass of control parameters
ctrl = mt.InductionMotorVectorCtrl(pars) 	# Sensorless controller

# Create a simulation object, simulate, and plot example figures
sim = mt.Simulation(mdl, ctrl)
sim.simulate()
mt.plot(sim)
```
This example applies the default settings. However, the drive system, controller, reference sequences etc. are easy to configure, see the folder `examples` for example scripts. New system models and controllers can be developed using the existing ones as templates. More features will be added later.

The documentation is available here:

https://aalto-electric-drives.github.io/motulator/

Acknowledgement
---------------
This project has been sponsored by ABB Oy. The example control methods included in this repository are based on published algorithms (available in textbooks and scientific articles). They do not present any proprietary control software.