gflownet.envs.alaninedipeptide

Attributes

path_to_data

Classes

AlanineDipeptide

Initializes a ContinuousCube environent.

Module Contents

class gflownet.envs.alaninedipeptide.AlanineDipeptide(path_to_dataset, url_to_dataset, **kwargs)

Bases: gflownet.envs.ctorus.ContinuousTorus

Initializes a ContinuousCube environent.

Parameters:

• ndim (int) – Dimensionality of the torus

• length_traj (int) – Fixed length of the trajectory.

• n_comp (int) – Number of components in the mixture of von Mises distributions used to sample angle increments.

• policy_encoding_dim_per_angle (int) – Dimensionality of the policy encodings of the angles.

• vonmises_min_concentration (float) – Minimum value allowed for the concentration parameter of the von Mises distributions.

• fixed_distr_params (dict) – Dictionary of parameters of the von Mises distribution that defines the fixed distribution of the environment. It must contain two keys with float values: vonmises_mean and vonmises_concentration.

• random_distr_params (dict) – Dictionary of parameters of the von Mises distribution that defines the random distribution of the environment. It must contain two keys with float values: vonmises_mean and vonmises_concentration.

atom_positions_dataset

conformer

sync_conformer_with_state(state=None)

Parameters:

state (List)

states2proxy(states)

Prepares a batch of states in “environment format” for the proxy: each state is a vector of length n_dim where each value is an angle in radians. The n_actions item is removed. This transformation is obtained from the parent states2proxy.

Important: this method returns a numpy array, unlike in most other environments.

Parameters:

states (list or tensor) – A batch of states in environment format, either as a list of states or as a single tensor.

Returns:

A numpy array containing all the states in the batch.

Return type:

numpy.typing.NDArray

gflownet.envs.alaninedipeptide.path_to_data