ipsuite.configuration_generation package¶

Submodules¶

ipsuite.configuration_generation.packmol module¶

Use packmole to create a periodic box

class ipsuite.configuration_generation.packmol.MultiPackmol(*args, **kwargs)[source]¶

Bases: Packmol

Create multiple configurations with packmol.

This Node generates multiple configurations with packmol. This is best used in conjunction with Smiles2Conformers:

Attributes¶

n_configurationsint: Number of configurations to create.
seedint: Seed for the random number generator.

Notes¶

Output structures should be relaxed before further use.

Example¶

>>> import ipsuite as ips
>>> project = ips.Project()
>>> with project:
...     bf4 = ips.Smiles2Conformers(
...         smiles='[B-](F)(F)(F)F', numConfs=10
...     )
...     bmim = ips.Smiles2Conformers(
...         smiles='CCCCN1C=C[N+](=C1)C',
...         numConfs=10
...     )
...     molecules = ips.MultiPackmol(
...         data=[bf4.frames, bmim.frames],
...         count=[1, 1], density=1210, n_configurations=10
...     )
...     box = ips.MultiPackmol(
...         data=[molecules.frames], count=[10], density=1210, n_configurations=1
...     )
>>> project.build()

count: list¶

data: list[list[ase.Atoms]]¶

density: float¶

n_configurations: int¶

run()[source]¶

seed: int = 42¶

class ipsuite.configuration_generation.packmol.Packmol(*args, **kwargs)[source]¶

Bases: IPSNode

Create a box with packmol.

Attributes¶

data: list[list[ase.Atoms]]: For each entry in the list the last ase.Atoms object is used to create the new structure.
data_ids: list[int]: The id of the data to use for each entry in data. If None the last entry. Has to be the same length as data. data: [[A], [B]], [-1, 3] -> [A[-1], B[3]]
count: list[int]: Number of molecules to add for each entry in data.
tolerancefloat: Tolerance for the distance of atoms in angstrom.
densityfloat: Density of the system in kg/m^3. Either density or box is required.
pbcbool: If True the periodic boundary conditions are set for the generated structure and the box used by packmol is scaled by the tolerance, to avoid overlapping atoms with periodic boundary conditions.

Notes¶

Output structures should be relaxed before further use.

count: list¶

data: list[list[Atoms]]¶

data_ids: list[int] = None¶

density: float¶

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

pbc: bool = True¶

run()[source]¶

tolerance: float = 2.0¶

ipsuite.configuration_generation.smiles_to_atoms module¶

class ipsuite.configuration_generation.smiles_to_atoms.Smiles2Atoms(*, name: str | None = None, always_changed: bool = False, smiles: str, seed: int = 1234, frames_path: pathlib.Path = PosixPath('$nwd$/frames.h5'), molecule_image_path: pathlib.Path = PosixPath('$nwd$/molecule.png'))[source]¶

Bases: IPSNode

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

molecule_image_path: Path = PosixPath('$nwd$/molecule.png')¶

run()[source]¶

seed: int = 1234¶

smiles: str¶

class ipsuite.configuration_generation.smiles_to_atoms.Smiles2Conformers(*args, **kwargs)[source]¶

Bases: IPSNode

Generate molecular conformers from a SMILES string.

Attributes¶

smilesstr: The SMILES string representing the molecule.
numConfsint: The number of conformers to generate.
seedint, optional: Random seed for conformer generation (default is 42).
maxAttemptsint, optional: Maximum number of attempts to generate conformers (default is 1000).

Methods¶

frameslist of ase.Atoms: Property to load and return the generated conformers as a list of ASE Atoms.

Notes¶

Instead of creating one composite smile like [B-](F)(F)(F)F.CCCCN1C=C[N+](=C1)C create two molecules and use MultiPackmol to generate the single molecule. This will avoid overlapping structures.

Examples¶

>>> with project:
...     methanol_conformers = ips.Smiles2Conformers(smiles="CO", numConfs=5)
>>> project.repro()
>>> frames = methanol_conformers.frames
>>> print(f"Generated {len(frames)} conformers.")
Generated 5 conformers.

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

maxAttempts: int = 1000¶

molecule_image_path: Path = PosixPath('$nwd$/molecule.png')¶

numConfs: int¶

run()[source]¶

seed: int = 42¶

smiles: str¶

Module contents¶

Module for generating new configurations based on smiles.

class ipsuite.configuration_generation.MultiPackmol(*args, **kwargs)[source]¶

Bases: Packmol

Create multiple configurations with packmol.

This Node generates multiple configurations with packmol. This is best used in conjunction with Smiles2Conformers:

Attributes¶

n_configurationsint: Number of configurations to create.
seedint: Seed for the random number generator.

Notes¶

Output structures should be relaxed before further use.

Example¶

>>> import ipsuite as ips
>>> project = ips.Project()
>>> with project:
...     bf4 = ips.Smiles2Conformers(
...         smiles='[B-](F)(F)(F)F', numConfs=10
...     )
...     bmim = ips.Smiles2Conformers(
...         smiles='CCCCN1C=C[N+](=C1)C',
...         numConfs=10
...     )
...     molecules = ips.MultiPackmol(
...         data=[bf4.frames, bmim.frames],
...         count=[1, 1], density=1210, n_configurations=10
...     )
...     box = ips.MultiPackmol(
...         data=[molecules.frames], count=[10], density=1210, n_configurations=1
...     )
>>> project.build()

count: list¶

data: list[list[ase.Atoms]]¶

density: float¶

n_configurations: int¶

run()[source]¶

seed: int = 42¶

class ipsuite.configuration_generation.Packmol(*args, **kwargs)[source]¶

Bases: IPSNode

Create a box with packmol.

Attributes¶

data: list[list[ase.Atoms]]: For each entry in the list the last ase.Atoms object is used to create the new structure.
data_ids: list[int]: The id of the data to use for each entry in data. If None the last entry. Has to be the same length as data. data: [[A], [B]], [-1, 3] -> [A[-1], B[3]]
count: list[int]: Number of molecules to add for each entry in data.
tolerancefloat: Tolerance for the distance of atoms in angstrom.
densityfloat: Density of the system in kg/m^3. Either density or box is required.
pbcbool: If True the periodic boundary conditions are set for the generated structure and the box used by packmol is scaled by the tolerance, to avoid overlapping atoms with periodic boundary conditions.

Notes¶

Output structures should be relaxed before further use.

count: list¶

data: list[list[Atoms]]¶

data_ids: list[int] = None¶

density: float¶

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

pbc: bool = True¶

run()[source]¶

tolerance: float = 2.0¶

class ipsuite.configuration_generation.Smiles2Atoms(*, name: str | None = None, always_changed: bool = False, smiles: str, seed: int = 1234, frames_path: pathlib.Path = PosixPath('$nwd$/frames.h5'), molecule_image_path: pathlib.Path = PosixPath('$nwd$/molecule.png'))[source]¶

Bases: IPSNode

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

molecule_image_path: Path = PosixPath('$nwd$/molecule.png')¶

run()[source]¶

seed: int = 1234¶

smiles: str¶

class ipsuite.configuration_generation.Smiles2Conformers(*args, **kwargs)[source]¶

Bases: IPSNode

Generate molecular conformers from a SMILES string.

Attributes¶

smilesstr: The SMILES string representing the molecule.
numConfsint: The number of conformers to generate.
seedint, optional: Random seed for conformer generation (default is 42).
maxAttemptsint, optional: Maximum number of attempts to generate conformers (default is 1000).

Methods¶

frameslist of ase.Atoms: Property to load and return the generated conformers as a list of ASE Atoms.

Notes¶

Instead of creating one composite smile like [B-](F)(F)(F)F.CCCCN1C=C[N+](=C1)C create two molecules and use MultiPackmol to generate the single molecule. This will avoid overlapping structures.

Examples¶

>>> with project:
...     methanol_conformers = ips.Smiles2Conformers(smiles="CO", numConfs=5)
>>> project.repro()
>>> frames = methanol_conformers.frames
>>> print(f"Generated {len(frames)} conformers.")
Generated 5 conformers.

property frames: list[Atoms]¶

frames_path: Path = PosixPath('$nwd$/frames.h5')¶

maxAttempts: int = 1000¶

molecule_image_path: Path = PosixPath('$nwd$/molecule.png')¶

numConfs: int¶

run()[source]¶

seed: int = 42¶

smiles: str¶

class ipsuite.configuration_generation.Smiles2Gromacs(*args, **kwargs)[source]¶

Bases: IPSNode

Gromacs Node.

Attributes¶

smiles: list[str]: List of SMILES strings for the molecules to be packed.
count: list[int]: Number of each molecule to pack.
labels: list[str]: List of 3-letter labels for each molecule.
density: float: Density of the packed box in g/cm^3.
mdp_files: list[str | pathlib.Path]: List of paths to the Gromacs MDP files.
config_files: list[str | pathlib.Path]: Same like mdp_files but in the json or yaml format. These will run BEFORE the MDP files.
itp_files: list[str | None]|None: if given, for each label either the path to the ITP file or None. The order must match the order of the labels.
pdb_files: list[str | pathlib.Path]|None: if given, for each label either the path to the PDB file or None. The order must match the order of the labels.
production_indices: list[int]|None: The gromacs runs that should be stored in the trajectory file. If None, the last run is stored. The order is always the same as the order of the MDP files.

Installation¶

To install the required software, run the following commands:

conda install conda-forge::gromacs
conda install conda-forge::acpype
pip install MDAnalysis pyedr

cleanup: bool = True¶

config_files: Sequence[str | Path]¶

count: list[int]¶

density: float¶

property frames: list[Atoms]¶

fudgeLJ: float = 1.0¶

fudgeQQ: float = 1.0¶

itp_files: Sequence[str | Path | None]¶

labels: list[str]¶

maxwarn: int = 0¶

mdp_files: Sequence[str | Path]¶

output_dir: Path = PosixPath('$nwd$/gromacs')¶

pdb_files: Sequence[str | Path | None]¶

production_indices: list[int] = None¶

run()[source]¶

smiles: list[str]¶

tolerance: float = 2.0¶

traj_file: list[Atoms] = PosixPath('$nwd$/structures.h5')¶