pantea package

Subpackages

• pantea.atoms package
  • Submodules
  • pantea.atoms.box module
    • Box
      • Box.apply_pbc()
      • Box.dtype
      • Box.from_list()
      • Box.lattice
      • Box.length
      • Box.lx
      • Box.ly
      • Box.lz
      • Box.volume
      • Box.wrap_into_box()
  • pantea.atoms.distance module
    • StructureInterface
      • StructureInterface.lattice
      • StructureInterface.positions
    • calculate_distances()
  • pantea.atoms.element module
    • ElementMap
      • ElementMap.atom_type_to_element
      • ElementMap.element_to_atom_type
      • ElementMap.element_to_atomic_number
      • ElementMap.from_list()
      • ElementMap.get_atom_type_from_element()
      • ElementMap.get_atomic_mass_from_element()
      • ElementMap.get_atomic_number_from_element()
      • ElementMap.get_element_from_atom_type()
      • ElementMap.get_element_from_atomic_number()
      • ElementMap.get_masses_from_structure()
      • ElementMap.unique_elements
    • StructureInterface
      • StructureInterface.atom_types
      • StructureInterface.element_map
  • pantea.atoms.neighbor module
    • Neighbor
      • Neighbor.from_structure()
      • Neighbor.masks
      • Neighbor.r_cutoff
    • StructureInterface
      • StructureInterface.lattice
      • StructureInterface.positions
  • pantea.atoms.structure module
    • Structure
      • Structure.add_energy_offset()
      • Structure.as_kernel_args()
      • Structure.atom_types
      • Structure.box
      • Structure.charges
      • Structure.dtype
      • Structure.element_map
      • Structure.energies
      • Structure.forces
      • Structure.from_ase()
      • Structure.from_dict()
      • Structure.get_elements()
      • Structure.get_forces_per_element()
      • Structure.get_positions_per_element()
      • Structure.get_unique_elements()
      • Structure.lattice
      • Structure.natoms
      • Structure.positions
      • Structure.remove_energy_offset()
      • Structure.select()
      • Structure.to_ase()
      • Structure.to_dict()
      • Structure.total_charge
      • Structure.total_energy
    • StructureAsKernelArgs
      • StructureAsKernelArgs.atom_types
      • StructureAsKernelArgs.element_map
      • StructureAsKernelArgs.lattice
      • StructureAsKernelArgs.positions
      • StructureAsKernelArgs.total_energy
  • Module contents
    • Box
      • Box.apply_pbc()
      • Box.dtype
      • Box.from_list()
      • Box.lattice
      • Box.length
      • Box.lx
      • Box.ly
      • Box.lz
      • Box.volume
      • Box.wrap_into_box()
    • ElementMap
      • ElementMap.atom_type_to_element
      • ElementMap.element_to_atom_type
      • ElementMap.element_to_atomic_number
      • ElementMap.from_list()
      • ElementMap.get_atom_type_from_element()
      • ElementMap.get_atomic_mass_from_element()
      • ElementMap.get_atomic_number_from_element()
      • ElementMap.get_element_from_atom_type()
      • ElementMap.get_element_from_atomic_number()
      • ElementMap.get_masses_from_structure()
      • ElementMap.unique_elements
    • Neighbor
      • Neighbor.from_structure()
      • Neighbor.masks
      • Neighbor.r_cutoff
    • Structure
      • Structure.add_energy_offset()
      • Structure.as_kernel_args()
      • Structure.atom_types
      • Structure.box
      • Structure.charges
      • Structure.dtype
      • Structure.element_map
      • Structure.energies
      • Structure.forces
      • Structure.from_ase()
      • Structure.from_dict()
      • Structure.get_elements()
      • Structure.get_forces_per_element()
      • Structure.get_positions_per_element()
      • Structure.get_unique_elements()
      • Structure.lattice
      • Structure.natoms
      • Structure.positions
      • Structure.remove_energy_offset()
      • Structure.select()
      • Structure.to_ase()
      • Structure.to_dict()
      • Structure.total_charge
      • Structure.total_energy
    • calculate_distances()
• pantea.datasets package
  • Submodules
  • pantea.datasets.dataset module
    • DataSourceInterface
      • DataSourceInterface.read_structures()
    • Dataset
      • Dataset.cache
      • Dataset.datasource
      • Dataset.from_runner()
      • Dataset.persist
      • Dataset.preload()
  • pantea.datasets.runner module
    • RunnerDataSource
      • RunnerDataSource.read_structures()
  • Module contents
    • Dataset
      • Dataset.cache
      • Dataset.datasource
      • Dataset.from_runner()
      • Dataset.persist
      • Dataset.preload()
    • RunnerDataSource
      • RunnerDataSource.read_structures()
• pantea.descriptors package
  • Subpackages
    • pantea.descriptors.acsf package
      • Submodules
      • pantea.descriptors.acsf.acsf module
      • pantea.descriptors.acsf.angular module
      • pantea.descriptors.acsf.cutoff module
      • pantea.descriptors.acsf.radial module
      • pantea.descriptors.acsf.symmetry module
      • Module contents
  • Submodules
  • pantea.descriptors.scaler module
    • DescriptorScaler
      • DescriptorScaler.check_warnings()
      • DescriptorScaler.fit()
      • DescriptorScaler.from_type()
      • DescriptorScaler.initialize_warnings()
      • DescriptorScaler.load()
      • DescriptorScaler.partial_fit()
      • DescriptorScaler.save()
      • DescriptorScaler.scale_max
      • DescriptorScaler.scale_min
    • ScaleRange
      • ScaleRange.max_value
      • ScaleRange.min_value
    • ScalerParams
      • ScalerParams.dimension
      • ScalerParams.maxval
      • ScalerParams.mean
      • ScalerParams.minval
      • ScalerParams.nsamples
      • ScalerParams.sigma
    • ScalerWarnings
      • ScalerWarnings.max_number_of_warnings
      • ScalerWarnings.number_of_warnings
  • Module contents
    • ACSF
    • AtomCenteredSymmetryFunction
      • AtomCenteredSymmetryFunction.angular_symmetry_functions
      • AtomCenteredSymmetryFunction.central_element
      • AtomCenteredSymmetryFunction.grad()
      • AtomCenteredSymmetryFunction.num_angular_symmetry_functions
      • AtomCenteredSymmetryFunction.num_radial_symmetry_functions
      • AtomCenteredSymmetryFunction.num_symmetry_functions
      • AtomCenteredSymmetryFunction.r_cutoff
      • AtomCenteredSymmetryFunction.radial_symmetry_functions
    • DescriptorScaler
      • DescriptorScaler.check_warnings()
      • DescriptorScaler.fit()
      • DescriptorScaler.from_type()
      • DescriptorScaler.initialize_warnings()
      • DescriptorScaler.load()
      • DescriptorScaler.partial_fit()
      • DescriptorScaler.save()
      • DescriptorScaler.scale_max
      • DescriptorScaler.scale_min
    • ScalerParams
      • ScalerParams.dimension
      • ScalerParams.maxval
      • ScalerParams.mean
      • ScalerParams.minval
      • ScalerParams.nsamples
      • ScalerParams.sigma
• pantea.models package
  • Subpackages
    • pantea.models.nn package
      • Submodules
      • pantea.models.nn.activation module
      • pantea.models.nn.initializer module
      • pantea.models.nn.model module
      • Module contents
  • Module contents
• pantea.potentials package
  • Subpackages
    • pantea.potentials.nnp package
      • Submodules
      • pantea.potentials.nnp.atomic_potential module
      • pantea.potentials.nnp.energy module
      • pantea.potentials.nnp.force module
      • pantea.potentials.nnp.gradient_descent module
      • pantea.potentials.nnp.kalman_filter module
      • pantea.potentials.nnp.metrics module
      • pantea.potentials.nnp.potential module
      • pantea.potentials.nnp.settings module
      • pantea.potentials.nnp.trainer module
      • Module contents
  • Module contents
• pantea.simulation package
  • Submodules
  • pantea.simulation.lennard_jones module
    • LJPotential
      • LJPotential.compute_forces()
    • LJPotentialParams
      • LJPotentialParams.epsilon
      • LJPotentialParams.sigma
  • pantea.simulation.molecular_dynamics module
    • MDSimulator
      • MDSimulator.repr_physical_params()
      • MDSimulator.simulate_one_step()
      • MDSimulator.verlet_integration()
  • pantea.simulation.monte_carlo module
    • MCSimulator
      • MCSimulator.metropolis_algorithm()
      • MCSimulator.repr_physical_params()
      • MCSimulator.simulate_one_step()
    • PotentialInterface
      • PotentialInterface.compute_forces()
  • pantea.simulation.simulate module
    • MDSystemInterface
      • MDSystemInterface.potential
      • MDSystemInterface.structure
    • PotentialInterface
      • PotentialInterface.compute_forces()
    • SimulatorInterface
      • SimulatorInterface.repr_physical_params()
      • SimulatorInterface.simulate_one_step()
      • SimulatorInterface.step
    • simulate()
  • pantea.simulation.system module
    • PotentialInterface
      • PotentialInterface.compute_forces()
    • System
      • System.box
      • System.compute_forces()
      • System.forces
      • System.from_structure()
      • System.generate_random_velocities()
      • System.get_center_of_mass_position()
      • System.get_center_of_mass_velocity()
      • System.get_elements()
      • System.get_kinetic_energy()
      • System.get_potential_energy()
      • System.get_pressure()
      • System.get_temperature()
      • System.get_total_energy()
      • System.masses
      • System.natoms
      • System.positions
      • System.potential
      • System.structure
      • System.update_forces_from_positions()
      • System.update_total_potential_energy_from_positions()
      • System.velocities
  • pantea.simulation.thermostat module
    • BrendsenThermostat
      • BrendsenThermostat.get_rescaled_velocities()
    • BrendsenThermostatParams
      • BrendsenThermostatParams.current_temperature
      • BrendsenThermostatParams.target_temperature
      • BrendsenThermostatParams.time_constant
      • BrendsenThermostatParams.time_step
    • MDSimulatorInterface
      • MDSimulatorInterface.time_step
    • SystemInterface
      • SystemInterface.get_temperature()
      • SystemInterface.velocities
  • Module contents
    • BrendsenThermostat
      • BrendsenThermostat.get_rescaled_velocities()
    • LJPotential
      • LJPotential.compute_forces()
    • MCSimulator
      • MCSimulator.metropolis_algorithm()
      • MCSimulator.repr_physical_params()
      • MCSimulator.simulate_one_step()
    • MDSimulator
      • MDSimulator.repr_physical_params()
      • MDSimulator.simulate_one_step()
      • MDSimulator.verlet_integration()
    • System
      • System.box
      • System.compute_forces()
      • System.forces
      • System.from_structure()
      • System.generate_random_velocities()
      • System.get_center_of_mass_position()
      • System.get_center_of_mass_velocity()
      • System.get_elements()
      • System.get_kinetic_energy()
      • System.get_potential_energy()
      • System.get_pressure()
      • System.get_temperature()
      • System.get_total_energy()
      • System.masses
      • System.natoms
      • System.positions
      • System.potential
      • System.structure
      • System.update_forces_from_positions()
      • System.update_total_potential_energy_from_positions()
      • System.velocities
    • simulate()
• pantea.utils package
  • Submodules
  • pantea.utils.attribute module
    • asarray()
    • set_as_attribute()
  • pantea.utils.batch module
    • create_batch()
  • pantea.utils.compare module
    • compare()
  • pantea.utils.profiler module
    • Profiler
      • Profiler.get_dataframe()
      • Profiler.profile()
    • Timer
    • timer()
  • pantea.utils.tokenize module
    • tokenize()
  • Module contents
    • Profiler
      • Profiler.get_dataframe()
      • Profiler.profile()

Submodules

pantea.config module

pantea.logger module

class pantea.logger.Logger(level=logging.WARNING, filename=None)

Bases: object

An utility logger class which allows more tweaks than the standard python logging.

debug(msg, *args, **kwargs)

Return type

None

error(msg, exception=None, *args, **kwargs)

Return type

None

info(msg, *args, **kwargs)

Return type

None

set_level(level)

Set the console logging level.

Parameters

level – INFO, WARNING, ERROR, and DEBUG

Return type

None

warn(msg, *args, **kwargs)

Return type

None

warning(msg, *args, **kwargs)

Return type

None

class pantea.logger.LoggingContextManager(level)

Bases: object

This utility class allows to monitor logging messages with different level (e.g. INFO or DEBUG) for a particular section of the scripts.

pantea.logger.set_logging_level(level)

Set the global logging level

Parameters

level (int (logging)) – INFO, WARNING, ERROR, and DEBUG

Return type

None

pantea.pytree module

class pantea.pytree.BaseJaxPytreeDataClass

Bases: object

Here we specify exactly which components of a dataclass should be treated as static and which should be treated as dynamic (array) attributes.

The hash method then it would only based on the static attributes and used for JIT re-compilation if they change.

Warning

It must be noted that we have to define first dynamic values (as tuple) and then static values (as dict) in child class constructor (same for dataclasses).

Registering the class to jax pytree node is also required.

Must be used only for dataclasses.

See https://jax.readthedocs.io/en/latest/faq.html#how-to-use-jit-with-methods

pantea.pytree.register_jax_pytree_node(cls)

Register the input class as internal JAX pytree node.

Return type

None

pantea.types module

class pantea.types.DataType(FLOATX=<class 'jax.numpy.float64'>, INT=<class 'jax.numpy.int32'>, UINT=<class 'jax.numpy.uint32'>, INDEX=<class 'jax.numpy.int32'>)

Bases: object

A configuration for array data type.

It is globally used as default dtype for arrays, indices, etc. User can modify any default dtype, for example, via setting the global floating point precision (FLOATX) to a single (float32) or double (float64).

FLOATX

alias of float64

INDEX

alias of int32

INT

alias of int32

UINT

alias of uint32

pantea.units module

class pantea.units.PhysicalUnits(BOLTZMANN_CONSTANT, TO_ANGSTROM, TO_PICO_SECOND, TO_BAR, TO_ELECTRON_VOLT, TO_ATOMIC_MASS, FROM_KCAL_PER_MOL=None)

Bases: object

Physical constants for units conversions.

BOLTZMANN_CONSTANT: float

FROM_ANGSTROM: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_ATOMIC_MASS: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_BAR: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_ELECTRON_VOLT: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_FEMTO_SECOND: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_GIGA_PASCAL: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_KCAL_PER_MOL: float = None

FROM_KILO_BAR: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_NANO_METER: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_NANO_SECOND: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

FROM_PICO_SECOND: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_ANGSTROM: float

TO_ATMOSPHERE: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_ATOMIC_MASS: float

TO_BAR: float

TO_ELECTRON_VOLT: float

TO_FEMTO_SECOND: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_GIGA_PASCAL: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_KCAL_PER_MOL: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_KILO_BAR: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_NANO_METER: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_NANO_SECOND: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_PASCAL: float = Field(name='FROM_KCAL_PER_MOL',type=<class 'float'>,default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=False,hash=None,compare=True,metadata=mappingproxy({}),_field_type=_FIELD)

TO_PICO_SECOND: float

Module contents

Pantea is an optimized Python library on basis of Google JAX that enables development of machine learning inter-atomic potentials for use in computational physics, chemistry, and material science. These potentials are necessary for conducting large-scale molecular dynamics simulations of complex materials with ab initio accuracy.