Skip to main content

Device Modeling Toolkit Core

Project description

DMT-core

pyversion Build Status Coverage Code style: black status

logo

DeviceModelingToolkit (DMT) is a Python tool targeted at helping modeling engineers extract model parameters, run circuit and TCAD simulations and automate their infrastructure.

See the DMT-website for further information.

Usage

Installation to virtual environment

After installing python 3.8 or later, create a virtual environment and install the release version using

    python3 -m pip install DMT-core[full]

For more information have a look at our installation guide

Currently, DMT is developed mostly on Ubuntu using Python 3.10. So for the easiest install this is the best supported platform. If you want or have to use Windows and MacOS there may be more dependency and installation issues, although needed projects we use support these platforms. Please report these issues to us. In our installation guide, we collect guides to solve the already known issues.

Full docker container

DMT is tested inside a docker container and this container can be used to run python/DMT scripts locally on your machine. See docker/dmt for an example bash script to run a file. Notice the configuration, this is needed so that simulation results and read measurement files persist on your host machine and do not vanish each time the container is closed.

For more information have a look at our docker guide

Questions, bugs and feature requests

If you have any questions or issues regarding DMT, we kindly ask you to contact us. Either mail us directly or open an issue here. There we have prepared several templates for the description:

Authors

Contributing

More contributors and merge-requests are always welcome. When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change.

Contact Markus or Mario, if you are interested to join the team permanently.

Pull Request Process

If you want to supply a new feature, you have implemented in your fork, to DMT, we are looking forward to your merge request. There we have a template for the merge request, including a checklist of suggested steps.

The steps are:

  1. Implement the new feature
  2. Add test cases for the new feature with a large coverage
  3. Add new python dependencies to setup.py
  4. If a interface is used, add a Dockerfile in which the interfaced software is installed and run the tests inside this Dockerfile
  5. Add additional documentation to the new features you implemented in the code and the documentation.
  6. Format the code using black
  7. Update the CHANGELOG with your changes and increase the version numbers in the changed files to the new version that this Pull Request would represent. The versioning scheme we use is SemVer.

License

This project is licensed under GLP-v3-or-later

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DMT_core-1.7.0.tar.gz (208.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

DMT_core-1.7.0-py3-none-any.whl (242.2 kB view details)

Uploaded Python 3

File details

Details for the file DMT_core-1.7.0.tar.gz.

File metadata

  • Download URL: DMT_core-1.7.0.tar.gz
  • Upload date:
  • Size: 208.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for DMT_core-1.7.0.tar.gz
Algorithm Hash digest
SHA256 eccbcc98976cdf10bea1dcb535593a09befaf8672e54e3d220e2931a416f6c19
MD5 3bdb4e4a02226ad7b265fd32bd9900de
BLAKE2b-256 fdf346ec1b19cdc5ef986f4f78e4273e1d22d649e1e692d6bd284d1d071a939d

See more details on using hashes here.

File details

Details for the file DMT_core-1.7.0-py3-none-any.whl.

File metadata

  • Download URL: DMT_core-1.7.0-py3-none-any.whl
  • Upload date:
  • Size: 242.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for DMT_core-1.7.0-py3-none-any.whl
Algorithm Hash digest
SHA256 edd9da2b8cb6f345b78ae675f3145eef66c573f4cc3e6bc3913144d4771fcd68
MD5 86b5d3b1da2dae483138c9d5659af3bd
BLAKE2b-256 cb1d67ebecd8d14588b56675fb8d3f238059d69121eb36d3e250fd242d738d6d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page