From dalke at dalkescientific.com  Mon Jul  4 05:11:31 2022
From: dalke at dalkescientific.com (Andrew Dalke)
Date: Mon, 4 Jul 2022 11:11:31 +0200
Subject: [chemfp] chemfp 4.0
Message-ID: <9DDC26D8-154F-4087-BA6C-6A65CFE1707F@dalkescientific.com>

Hi chemfp mailing list subscribers!

  I've recently released chemfp 4.0, with support for several diversity selection algorithms, and an improved API for interactive use in a notebook environment.

The new diversity selection algorithms are MaxMin, sphere exclusion (both random and directed), and HeapSweep.

Of special note, The MaxMin algorithm has improved support for selecting diverse fingerprints from a set of candidates (eg, a vendor catalog) which must also be diverse from a set of references (eg, a corporate collection), which is over an order of magnitude faster than the standard MaxMin algorithm.

People who live in the Jupyter notebook will likely enjoy the new chemfp user experience. Most long-term actions support progress bars, chemfp's Python objects have more informative repr()s, search results added Pandas integration, and there are new high-level APIs that let you express a lot of functionality compactly.

See https://chemfp.readthedocs.io/en/latest/whatsnew.html for more details.

To install the pre-compiled package for Linux at no cost, use:

  python -m pip install chemfp -i https://chemfp.com/packages/

The Base License covers most in-house use of chemfp, though a few features are either limited or disabled and require a license key to unlock. For alternative licenses, including source code and no-cost academic licensing, see https://chemfp.com/license/ -- or try one of the re-formatted ChEMBL datasets at https://chemfp.com/datasets/ which include an embedded authorization key.

The tentative plan for chemfp 4.1 is to improve clustering support.

Best regards,

				Andrew
				dalke at dalkescientific.com