Skip to main content

A test-driven framework for formally validating scientific models against data.

Project description

Master Dev
Travis Travis
RTFD RTFD
Binder
Coveralls Coveralls
Requirements Requirements
Docker Build Status
Repos using Sciunit
Downloads from PyPI
SciUnit Logo

SciUnit: A Test-Driven Framework for Formally Validating Scientific Models Against Data

Concept

The conference paper

Documentation

Colab
Chapter 1 / Chapter 2 / Chapter 3 / Chapter 4 / Chapter 5 / Chapter 6 /

Basic Usage

my_model = MyModel(**my_args) # Instantiate a class that wraps your model of interest.  
my_test = MyTest(**my_params) # Instantiate a test that you write.  
score = my_test.judge() # Runs the test and return a rich score containing test results and more.  

Domain-specific libraries and information

NeuronUnit for neuron and ion channel physiology
See others here

Mailing List

There is a mailing list for announcements and discussion. Please join it if you are at all interested!

Contributors

  • Rick Gerkin, Arizona State University (School of Life Science)
  • Cyrus Omar, Carnegie Mellon University (Dept. of Computer Science)

Reproducible Research ID

RRID:SCR_014528

License

SciUnit is released under the permissive MIT license, requiring only attribution in derivative works. See the LICENSE file for terms.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

sciunit-0.2.2.4-py3-none-any.whl (76.4 kB view details)

Uploaded Python 3

File details

Details for the file sciunit-0.2.2.4-py3-none-any.whl.

File metadata

  • Download URL: sciunit-0.2.2.4-py3-none-any.whl
  • Upload date:
  • Size: 76.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.23.0 setuptools/51.0.0.post20201207 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.3

File hashes

Hashes for sciunit-0.2.2.4-py3-none-any.whl
Algorithm Hash digest
SHA256 61724156e41fba4411c4019b4aa3e21db0760c9b09d7f45633de0f81781ad3f3
MD5 52e1e3150bb12cc610f81ce91c6be30c
BLAKE2b-256 0b6f945b0f1f5ea76d4d7199f1d9e717866d3677d41c8393cccbec816c74d039

See more details on using hashes here.

Provenance

Supported by

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