batter.config.simulation.SimulationConfig

class batter.config.simulation.SimulationConfig(*, system_name: str, fe_type: ~typing.Literal['custom', 'rest', 'sdr', 'dd', 'sdr-rest', 'express', 'relative', 'uno', 'uno_com', 'uno_rest', 'self', 'uno_dd', 'dd-rest', 'asfe', 'md'], dec_int: ~typing.Literal['mbar', 'ti'] = 'mbar', remd: ~typing.Literal['yes', 'no'] = 'no', remd_nstlim: int = 100, slurm_header_dir: ~pathlib.Path = <factory>, infe: bool = False, p1: str = '', p2: str = '', p3: str = '', other_mol: ~typing.List[str] = <factory>, lipid_mol: ~typing.List[str] = <factory>, solv_shell: float | None = 15.0, rocklin_correction: ~typing.Literal['yes', 'no'] = 'no', release_eq: ~typing.List[float] = <factory>, ti_points: int | None = 0, lambdas: ~typing.List[float] = <factory>, component_windows: ~typing.Dict[str, ~typing.List[float]] = <factory>, sdr_dist: float | None = 0.0, dec_method: str | None = None, blocks: int = 0, unbound_threshold: ~typing.Annotated[float, ~annotated_types.Ge(ge=0)] = 8.0, analysis_start_step: ~typing.Annotated[int, ~annotated_types.Ge(ge=0)] = 0, n_bootstraps: ~typing.Annotated[int, ~annotated_types.Ge(ge=0)] = 0, lig_distance_force: float = 0.0, lig_angle_force: float = 0.0, lig_dihcf_force: float = 0.0, rec_com_force: float = 0.0, lig_com_force: float = 0.0, water_model: ~typing.Literal['SPCE', 'TIP4PEW', 'TIP3P', 'TIP3PF', 'OPC'] = 'TIP3P', buffer_x: float = 10.0, buffer_y: float = 10.0, buffer_z: float = 15.0, lig_buffer: float = 10.0, neutralize_only: ~typing.Literal['yes', 'no'] = 'no', cation: str = 'Na+', anion: str = 'Cl-', ion_conc: float = 0.15, hmr: ~typing.Literal['yes', 'no'] = 'no', enable_mcwat: ~typing.Literal['yes', 'no'] = 'yes', temperature: float = 298.15, eq_steps: int = 1000000, n_steps_dict: ~typing.Dict[str, int] = <factory>, l1_x: float | None = None, l1_y: float | None = None, l1_z: float | None = None, l1_range: float | None = None, min_adis: float | None = None, max_adis: float | None = None, ntpr: int = 100, ntwr: int = 10000, ntwe: int = 0, ntwx: int = 2500, cut: float = 9.0, gamma_ln: float = 1.0, barostat: ~typing.Literal[1, 2] = 2, dt: float = 0.004, all_atoms: ~typing.Literal['yes', 'no'] = 'no', receptor_ff: str = 'protein.ff14SB', ligand_ff: str = 'gaff2', lipid_ff: str = 'lipid21', ligand_dict: ~typing.Dict[str, ~typing.Any] = <factory>, rng: int = 0, ion_def: ~typing.List[~typing.Any] = <factory>, dic_n_steps: ~typing.Dict[str, int] = <factory>, rest: ~typing.List[float] = <factory>, neut: str = '', protein_align: str = 'name CA', receptor_segment: str | None = None, components: ~typing.List[str] = <factory>, component_lambdas: ~typing.Dict[str, ~typing.List[float]] = <factory>, membrane_simulation: bool = True)

Simulation configuration for ABFE/ASFE/RBFE workflows. Values are fed by RunConfig.resolved_sim_config(), which merges create: and fe_sim:.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
from_sections(create, fe, *[, protocol, ...])	Construct a SimulationConfig from run sections.
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema(by_alias, ref_template, ...)	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
to_dict()
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
system_name
fe_type
dec_int
remd
remd_nstlim
slurm_header_dir
infe
p1
p2
p3
other_mol
lipid_mol
solv_shell
rocklin_correction
release_eq
ti_points
lambdas
component_windows
sdr_dist
dec_method
blocks
unbound_threshold
analysis_start_step
n_bootstraps
lig_distance_force
lig_angle_force
lig_dihcf_force
rec_com_force
lig_com_force
water_model
buffer_x
buffer_y
buffer_z
lig_buffer
neutralize_only
cation
anion
ion_conc
hmr
enable_mcwat
temperature
eq_steps
n_steps_dict
l1_x
l1_y
l1_z
l1_range
min_adis
max_adis
ntpr
ntwr
ntwe
ntwx
cut
gamma_ln
barostat
dt
all_atoms
receptor_ff
ligand_ff
lipid_ff
ligand_dict
rng
ion_def
dic_n_steps
rest
neut
protein_align
receptor_segment
components
component_lambdas
membrane_simulation