Skip to main content

AiiDA plugin for the Aurora platform.

Project description

Build Status Coverage Status Docs status PyPI version

aiida-aurora

AiiDA plugin for the Aurora project (autonomous robotic battery innovation platform). A collaboration between EPFL & Empa, within the BIG-MAP Stakeholder Initiative Call 2021.

Repository contents

See also the following video sequences from the 2019-05 AiiDA tutorial:

For more information, see the developer guide of your plugin.

Features

  • Add input files using SinglefileData:

    SinglefileData = DataFactory('singlefile')
    inputs['file1'] = SinglefileData(file='/path/to/file1')
    inputs['file2'] = SinglefileData(file='/path/to/file2')
    
  • Specify command line options via a python dictionary and DiffParameters:

    d = { 'ignore-case': True }
    DiffParameters = DataFactory('aurora')
    inputs['parameters'] = DiffParameters(dict=d)
    
  • DiffParameters dictionaries are validated using voluptuous. Find out about supported options:

    DiffParameters = DataFactory('aurora')
    print(DiffParameters.schema.schema)
    

Installation

pip install aiida-aurora
verdi quicksetup  # better to set up a new profile
verdi plugin list aiida.calculations  # should now show your calclulation plugins

Usage

Here goes a complete example of how to submit a test calculation using this plugin.

A quick demo of how to submit a calculation:

verdi daemon start     # make sure the daemon is running
cd examples
./example_01.py        # run test calculation
verdi process list -a  # check record of calculation

The plugin also includes verdi commands to inspect its data types:

verdi data aurora list
verdi data aurora export <PK>

Development

git clone https://github.com/epfl-theos/aiida-aurora .
cd aiida-aurora
pip install -e .[pre-commit,testing]  # install extra dependencies
pre-commit install  # install pre-commit hooks
pytest -v  # discover and run all tests

See the developer guide for more information.

License

MIT

Contact

francisco.ramirez@epfl.ch edan.bainglass@psi.ch giovanni.pizzi@psi.ch

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

aiida_aurora-0.3.2.tar.gz (120.2 kB view details)

Uploaded Source

Built Distribution

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

aiida_aurora-0.3.2-py3-none-any.whl (38.5 kB view details)

Uploaded Python 3

File details

Details for the file aiida_aurora-0.3.2.tar.gz.

File metadata

  • Download URL: aiida_aurora-0.3.2.tar.gz
  • Upload date:
  • Size: 120.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.31.0

File hashes

Hashes for aiida_aurora-0.3.2.tar.gz
Algorithm Hash digest
SHA256 f2ed0caac37da428321591bbef652f144c91ef9d07110e3cfd1a13c0c47522d0
MD5 3ca5c24cf930744bef5fa76313dce9ce
BLAKE2b-256 1f116b4f774f2947902c301d6f80b37042ed2df3f318a3d609b8f2e55b26c5a1

See more details on using hashes here.

File details

Details for the file aiida_aurora-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: aiida_aurora-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 38.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.31.0

File hashes

Hashes for aiida_aurora-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 bc88fd5d8679cfdae4d7e15fc44eb9b441ffa83cb9902329405e49812d59a2a0
MD5 797a5c292d5e228779b0a49952f7ae46
BLAKE2b-256 c1015437e080c4f4a0d526a9c48661f2344e1959980cb635b52cd0037522700f

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