poli
🧪, a library for discrete objective functionspoli
is a library of discrete objective functions for benchmarking optimization algorithms.
np.array
s of strings, outputs are np.array
s of floats.SMILES
and SELFIES
support for small molecule manipulation.To install poli
, we recommend creating a fresh conda environment
conda create -n poli-base python=3.9
conda activate poli-base
pip install git+https://github.com/MachineLearningLifeScience/poli.git@dev
To check if everything went well, you can run
$ python -c "from poli import create"
In this next example, we estimate the docking score of the example provided in dockstring
:
import numpy as np
from poli import objective_factory
problem = objective_factory.create(
name="dockstring",
target_name="drd2"
)
f, x0 = problem.black_box, problem.x0
y0 = f(x0)
# x0: [['C' 'C' '1' '=' 'C' '(' 'C', ...]] (i.e. Risperidone's SMILES)
# y0: 11.9
print(x0, y0)
If you use certain black boxes, we expect you to cite the relevant work. Check inside the documentation of each black box for the relevant references.
The main documentation site is hosted as a GitHub page here: https://machinelearninglifescience.github.io/poli-docs/
If you install the requirements-dev.txt
via
pip install -r requirements-dev.txt
then you will have access to sphinx
. You should be able to build the documentation by going to the docs folder and building it:
cd docs/
make html
Afterwards, you can enter the build
folder and open index.html
.