Skip to main content

This is the library for descriptors calculation, data preprocessing and AutoML.

Project description

NanoDescriptors is a Python library for automated descriptor generation, data preprocessing, and AutoML for nanomaterial property prediction (QSAR/QSPR). Main features Parses complex formulas (core‑shell @, composites -//, non‑stoichiometric, 19 material types)

Calculates >100 descriptors (electronic, thermodynamic, atomic‑mechanical, additive mixture descriptors)

Automatic data cleaning, encoding, skew correction, scaling

AutoML regression/classification with Optuna + SHAP/PLS/RFE feature selection + stacking ensembles

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nanodesclib-0.0.1.tar.gz (96.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nanodesclib-0.0.1-py3-none-any.whl (104.7 kB view details)

Uploaded Python 3

File details

Details for the file nanodesclib-0.0.1.tar.gz.

File metadata

  • Download URL: nanodesclib-0.0.1.tar.gz
  • Upload date:
  • Size: 96.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.11

File hashes

Hashes for nanodesclib-0.0.1.tar.gz
Algorithm Hash digest
SHA256 91ebc51f8770e9ecb0865acb7ec24c34bde25df5953a91f21bf7fad2bf7f8c27
MD5 997a47d61415f0de776c0b306bc7c6e5
BLAKE2b-256 7d0a11c9802ce79a67a552c27840a10c180c23c3ef73ea1c47ab7ad246d88a01

See more details on using hashes here.

File details

Details for the file nanodesclib-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: nanodesclib-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 104.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.11

File hashes

Hashes for nanodesclib-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a2fd3cf769e8fa9186ebd29f63e460c32bafa845805ab481f35294f51d924309
MD5 5d944db4f3e3b7bc1e4ea6abe55c40d7
BLAKE2b-256 e89b72b9edcf3a0d753a43d91db4df0ddfa4c20ceb3e9f084b6fe7999f0a05a1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page