Skip to main content

Project to perform uncertainty quantification of PhysiCell models

Project description

UQ-PhysiCell

pyABC logo

Run Unit Tests Documentation Status PyPI Python

UQ-PhysiCell is a comprehensive framework for performing uncertainty quantification and parameter calibration of PhysiCell models. It provides sophisticated tools for model analysis, calibration, and model selection.

Resources

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

uq_physicell-1.2.0.post1.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

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

uq_physicell-1.2.0.post1-py3-none-any.whl (1.1 MB view details)

Uploaded Python 3

File details

Details for the file uq_physicell-1.2.0.post1.tar.gz.

File metadata

  • Download URL: uq_physicell-1.2.0.post1.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for uq_physicell-1.2.0.post1.tar.gz
Algorithm Hash digest
SHA256 2d5f30b6f07cdda7e470730f1bde168f656f9962f6ea1330bb324613124eb602
MD5 b2020ce02493627b5010af6db44164a7
BLAKE2b-256 8a2bce06882d066188ebc639446f90cc1f406eb5252b3212d25d46dd1bc6954e

See more details on using hashes here.

File details

Details for the file uq_physicell-1.2.0.post1-py3-none-any.whl.

File metadata

File hashes

Hashes for uq_physicell-1.2.0.post1-py3-none-any.whl
Algorithm Hash digest
SHA256 969ea35e2d2e2749e6360b17944d9dde90a910c141b0d5312d2b80b3d3c0e369
MD5 79dae76b6645238e5c1a85007eb968c2
BLAKE2b-256 8d06e9ea946d4a2e3b725f41e9e9797c6b3dc24995dd5297827f4bec1043e4c8

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