malada.pipeline package

Submodules

malada.pipeline.pipeline module

Data generation Pipeline.

class malada.pipeline.pipeline.DataPipeline(parameters, crystal_structure_provider: Optional[malada.providers.crystalstructure.CrystalStructureProvider] = None, supercell_provider: Optional[malada.providers.supercell.SuperCellProvider] = None, dft_convergence_provider: Optional[malada.providers.dftconvergence.DFTConvergenceProvider] = None, md_performance_provider: Optional[malada.providers.mdperformance.MDPerformanceProvider] = None, md_provider: Optional[malada.providers.md.MDProvider] = None, snapshots_provider: Optional[malada.providers.snapshots.SnapshotsProvider] = None, ldos_configuration_provider: Optional[malada.providers.ldosconvergence.LDOSConvergenceProvider] = None, dft_provider: Optional[malada.providers.dft.DFTProvider] = None)

Bases: object

Uses providers to run an entire data pipeline, ending with the LDOS.

Parameters

  • parameters (malada.utils.parametes.Parameters) – Parameters used to create this object.

  • crystal_structure_provider (malada.CrystalStructureProvider) – Provider for crystal structures.

  • supercell_provider (malada.SuperCellProvider) – Provider for supercells (=atomic positions).

  • dft_convergence_provider (malada.DFTConvergenceProvider) – Provider for optimal DFT parameters (cutoff energy / k-grid)

  • md_performance_provider (malada.MDPerformanceProvider) – Provider for optimal MD performance (parallelization).

  • md_provider (malada.MDProvider) – Provider for MD trajectory and temperatures.

  • snapshots_provider (malada.SnapshotsProvider) – Provider of set of atomic positions from MD trajectory.

  • ldos_configuration_provider (malada.LDOSConvergenceProvider) – Provider for optimal LDOS calculation parameters (energy and k- grid).

  • dft_provider (malada.DFTProvider) – Provider for final DFT calculations and LDOS calculation

run()

Run a full data generation pipeline.

Module contents

Contains everything concerning the data pipeline itself.