Software Open Access
Major Release (v0.1.0)
Gym-lattice is an HP 2D Lattice Environment with a Gym-like API for the protein folding problem.
This is a Python library that formulates Lau and Dill's (1989) hydrophobic-polar two-dimensional lattice model as a reinforcement learning problem. It follows OpenAI Gym's API, easing integration for reinforcement learning solutions.
Features
render()
draws the chain on the command-line.Additionally, there is an option to set the penalty parameters for training the agent, this includes:
collision_penalty
): accounts for the time whenever the agent decides to assign a molecule to an already-occupied space; andtrap_penalty
): induces heavy deductions whenever the agent traps itself and cannot accomplish the task anymore.Tests
Exceptions
instead of asserts
when catching errors.pytest
and tox
.Name | Size | |
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ljvmiranda921/gym-lattice-v0.1.0.zip
md5:4a87c6e5aba51083c994281b23b66bbc |
49.3 kB | Download |
Lau, K.F. and Dill, K.A., 1989. A lattice statistical mechanics model of the conformational and sequence spaces of proteins. Macromolecules, 22(10), pp.3986-3997.
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