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.
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/)
- 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)
The easiest way to get started with agentMET4FOF is navigating to the folder in which you want to create a virtual Python environment (venv), create one, activate it, first install numpy, then install agentMET4FOF from PyPI.org and then work through the tutorials or examples. To do this, issue the following commands on your Shell:
$ cd /LOCAL/PATH/TO/ENVS $ python3 -m venv agentMET4FOF_venv $ source agentMET4FOF_venv/bin/activate (agentMET4FOF_venv) $ pip install numpy Collecting numpy ... Successfully installed numpy-... (agentMET4FOF_venv) $ pip install agentMET4FOF Collecting agentMET4FOF ... Successfully installed agentMET4FOF-... ... (agentMET4FOF_venv) $ python Python ... (default, ..., ...) [GCC ...] on ... Type "help", "copyright", "credits" or "license" for more information. >>> from agentMET4FOF_tutorials import tutorial_1_generator_agent >>> tutorial_1_generator_agent.main() Starting NameServer... Broadcast server running on 0.0.0.0:9091 NS running on 127.0.0.1:3333 (127.0.0.1) URI = PYRO:Pyro.NameServer@127.0.0.1:3333 INFO [2020-02-21 19:04:26.961014] (AgentController): INITIALIZED INFO [2020-02-21 19:04:27.032258] (Logger): INITIALIZED * Serving Flask app "agentMET4FOF.dashboard.Dashboard" (lazy loading) * Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Debug mode: off * Running on http://127.0.0.1:8050/ (Press CTRL+C to quit) ...
Now you can visit
http://127.0.0.1:8050/ with any Browser and watch the
SineGenerator agent you just spawned.
To get some insights and really get going please visit agentMET4FOF.readthedocs.io .
Get started developing
First clone the repository to your local machine as described here. To get started with your present Anaconda installation just go to Anaconda prompt, navigate to your local clone
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 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
Alternatively, watch the tutorial webinar here
- 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
- Implemented interactive web application with user interface
Screenshot of web visualization
In the event of agents not terminating cleanly, run
taskkill /f /im python.exe /t
in Windows Command Prompt to terminate all background python processes.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size agentMET4FOF-0.1.3-py3-none-any.whl (24.2 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size agentMET4FOF-0.1.3.tar.gz (22.9 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for agentMET4FOF-0.1.3-py3-none-any.whl