Metadata-Version: 2.1
Name: agentMET4FOF
Version: 0.1.1
Summary: A software package for the integration of metrological input into an agent-based system for the consideration of measurement uncertainty in current industrial manufacturing processes.
Home-page: https://github.com/bangxiangyong/agentMET4FOF
Author: Bang Xiang Yong, Björn Ludwig, Haris Lulic
Author-email: bxy20@cam.ac.uk
License: UNKNOWN
Keywords: uncertainty metrology MAS agent-based agents
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3
Description-Content-Type: text/markdown
Requires-Dist: ipykernel
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scikit-multiflow
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: seaborn
Requires-Dist: osbrain
Requires-Dist: dash
Requires-Dist: dash-cytoscape
Requires-Dist: networkx
Requires-Dist: multiprocess
Requires-Dist: h5py
Requires-Dist: requests
Requires-Dist: plotly

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# Multi-Agent System for Metrology for Factory of the Future (Met4FoF) Code
This is supported by European Metrology Programme for Innovation and Research (EMPIR) under the project Metrology for the Factory of the Future (Met4FoF), project number 17IND12. (https://www.ptb.de/empir2018/met4fof/home/)

About
---
 - How can metrological input be incorporated into an agent-based system for addressing uncertainty of machine learning in future manufacturing?
 - Includes agent-based simulation and implementation
 - Readthedocs documentation is available at (https://agentmet4fof.readthedocs.io)

Get started
---
First clone the repository to your local machine as described
[here](https://help.github.com/en/articles/cloning-a-repository). To get started
with your present *Anaconda* installation just go to *Anaconda
prompt*, navigate to your local clone

```shell
cd /your/local/folder/agentMet4FoF
```

and execute

```shell
conda env create --file environment.yml 
```

This will create an *Anaconda* virtual environment with all dependencies
satisfied. If you don't have *Anaconda* installed already follow [this guide
](https://docs.conda.io/projects/continuumio-conda/en/latest/user-guide/install/download.html)
first, then create the virtual environment as stated above and then proceed.

Alternatively, for non-conda environments, you can install the dependencies using pip
```
pip install -r requirements.txt
```

First take a look at the [tutorials](./tutorials/tutorial_1_generator_agent.py) and
[examples](./examples) or start hacking if you already are familiar with agentMET4FOF
and want to customize your agents' network.

Alternatively, watch the tutorial webinar [here](https://github.com/bangxiangyong/agentMET4FOF/releases/download/0.1.0/Met4FoF.MAS.webinar.mp4)

Updates
---
 - Implemented base class AgentMET4FOF with built-in agent classes DataStreamAgent, MonitorAgent
 - Implemented class AgentNetwork to start or connect to a agent server
 - Implemented with ZEMA prognosis of Electromechanical cylinder data set as use case 
   [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1326278.svg)](https://doi.org/10.5281/zenodo.1326278)
 - Implemented interactive web application with user interface

## Screenshot of web visualization
![Web Screenshot](docs/screenshot_met4fof.png)

Note
---
- In the event of agents not terminating cleanly, run

  ```python
  taskkill /f /im python.exe /t
  ```

  in Windows Command Prompt to terminate all background python processes.


