Skip to main content

Easy coarse-grained simulations with the SAFT-gamma Mie force field

Project description

# raaSAFT #
![raasaft-wide.jpg](https://bitbucket.org/repo/pn6BAR/images/2465645789-raasaft-wide.jpg)

###### Illustrative image courtesy of [www.frukt.no](frukt.no)

### What is raaSAFT? ###

* raaSAFT (pronounced "raw saft") is a Python framework for easy coarse-grained molecular dynamics simulations.
* raaSAFT runs with HOOMD-blue as a backend, so you can use GPU power. Initial support for using GROMACS has been added.
* raaSAFT uses the SAFT-gamma Mie force field, a coarse-graining method which is thermodynamically consistent, and not based on tuning to atomistic simulations
* Raasaft is a Norwegian word meaning "pure fruit syrup". Apart from the obvious saft <-> SAFT pun, "raa" means crude/raw/**coarse**, so it is twice as punny.

### Installing raaSAFT ###

**Dependencies:**

* raaSAFT uses HOOMD-blue, see the [HOOMD-blue install guide](https://codeblue.umich.edu/hoomd-blue/doc/page_install_guide.html).
* For now this is a dependency even if you want to run with GROMACS. The non-GPU version of HOOMD-blue is sufficient.
* Note that HOOMD-blue runs on Linux or Mac OSX. Windows is not supported.

**Simple installation:**

* System-wide install: `sudo pip install raasaft`
* Local installation: `pip install --user raasaft`

* To upgrade: add `--upgrade` after `install`

* To start using raaSAFT: make a new folder, enter it and run the command
`raasaft_init`
to add the helpful directories `tutorials/`, `replication/` and `mysaft/`.
* Read the "Running simulations" section below.

**Installation for advanced users / contributors:**

* Install dependencies. This includes HOOMD-blue and the Python packages `future` and `requests`.
* Clone this repo
* The `maint` branch should be as stable as the version on PyPi
* The `master` branch changes frequently and may not always be stable
* The `raasaft_init` command will not be in your path unless you put it there.

### Running simulations with raaSAFT ###
* Make sure you have run the `raasaft_init` command in the folder where you want to run your simulations.
* Let's call this folder "trysaft".
* Look at the README.txt file in "trysaft/tutorials/" for examples of how to use raaSAFT.
* In "trysaft/replication/" we include setups that can be used to replicate the findings of various papers.
* In "trysaft/mysaft/" you find an example of how to add your own models for new molecules.
* You can use these user-defined models with e.g.
`from mysaft.example import Example`
`ex = Example(count=1e3)`
* If you want to use these models in jobscripts in different directories, add the full path to the "trysaft" folder to your `PYTHONPATH` shell variable, e.g.:
`export PYTHONPATH=$PYTHONPATH:"$HOME/trysaft"`
* Contributions to raaSAFT with new models are always welcome, assuming the model has seen at least some level of validation.

### Bottled SAFT ###
You can get models (force field parameters) for 6000+ molecules from our database called Bottled SAFT: [www.bottledsaft.org](http://www.bottledsaft.org).
This web application provides scripts that implement the search result in raaSAFT for you!

### License ###
* The code is Free and Open Source software under the [MIT license](https://bitbucket.org/asmunder/raasaft/src/master/LICENSE.txt).

### Contribute ###
* All contributions are welcome!

### Contact ###
* Email Åsmund at aaervik@gmail.com

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

raaSAFT-0.6.2.tar.gz (138.2 kB view details)

Uploaded Source

Built Distribution

raaSAFT-0.6.2-py2.py3-none-any.whl (30.8 kB view details)

Uploaded Python 2Python 3

File details

Details for the file raaSAFT-0.6.2.tar.gz.

File metadata

  • Download URL: raaSAFT-0.6.2.tar.gz
  • Upload date:
  • Size: 138.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for raaSAFT-0.6.2.tar.gz
Algorithm Hash digest
SHA256 4bc393c784ed3d12e89b97da94b1b652755ce55c7cb13d7463d2ed446eca17e7
MD5 ca90d849549df5a0fb77dd04ed13e4de
BLAKE2b-256 cc91831cdc5ea939e85bc717305b7eb0b8b72cb623d30f8cfeb840f23fbd6ea4

See more details on using hashes here.

File details

Details for the file raaSAFT-0.6.2-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for raaSAFT-0.6.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 11a73e58e308525515dab2a5fdb98a49b223a16a9ef8a8ad824a280d8579761b
MD5 2f5539e5c1dc6b4382483eeafbd19e7b
BLAKE2b-256 768077a89aa4b7aed6947688af5b367adcc6cbc095841599fc774fb3a3412650

See more details on using hashes here.

Supported by

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