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

Project description

Master	Dev

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

Concept

The conference paper

Documentation

Chapter 1 / Chapter 2 / Chapter 3 /

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

Release history Release notifications | RSS feed

0.2.8

Jan 3, 2024

0.2.7

May 14, 2022

0.2.6

Feb 23, 2022

0.2.5.1

Aug 24, 2021

0.2.5 yanked

Aug 24, 2021

Reason this release was yanked:

build

0.2.4

May 4, 2021

0.2.3

Jan 31, 2021

0.2.2.4

Dec 29, 2020

This version

0.2.2.3

Jul 21, 2020

0.2.2.2

May 21, 2020

0.2.2.1

Apr 8, 2020

0.2.2

Feb 11, 2020

0.2.1.1

Aug 7, 2019

0.2.1

Jul 5, 2019

0.2.0.2

May 12, 2018

0.2.0.1

May 10, 2018

0.1.5.7

May 27, 2017

0.1.5.6

Apr 3, 2017

0.1.5.2

Jul 4, 2016

0.1.4.2

Oct 23, 2015

0.1.3.2

Sep 3, 2015

0.1.3.1

Jun 26, 2015

0.1.3

Jun 26, 2015

0.1.1

Nov 12, 2012

0.1.0

Nov 12, 2012

Download files

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

Source Distribution

sciunit-0.2.2.3.tar.gz (43.7 kB view details)

Uploaded Jul 21, 2020 Source

Built Distribution

sciunit-0.2.2.3-py3-none-any.whl (57.5 kB view details)

Uploaded Jul 21, 2020 Python 3

File details

Details for the file sciunit-0.2.2.3.tar.gz.

File metadata

Download URL: sciunit-0.2.2.3.tar.gz
Upload date: Jul 21, 2020
Size: 43.7 kB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.46.1 CPython/3.7.6

File hashes

Hashes for sciunit-0.2.2.3.tar.gz
Algorithm	Hash digest
SHA256	`96f7a6c7cd29e555a55630f62267ef22dc49dbb05e8e863d70d1588291916934`
MD5	`715c4dd15e4cd4b74c52f7fa809ec84e`
BLAKE2b-256	`80b981918102ed191c45b9c2aa4b6ed0d323126ffec9113b141f4cde7b379f9e`

See more details on using hashes here.

Provenance

File details

Details for the file sciunit-0.2.2.3-py3-none-any.whl.

File metadata

Download URL: sciunit-0.2.2.3-py3-none-any.whl
Upload date: Jul 21, 2020
Size: 57.5 kB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.46.1 CPython/3.7.6

File hashes

Hashes for sciunit-0.2.2.3-py3-none-any.whl
Algorithm	Hash digest
SHA256	`8d490bd19f2926d72a7dee464d48593180986ef3b57a3264663a0ca2b263667f`
MD5	`47222a5f930db9e25160b27a9458d1aa`
BLAKE2b-256	`a7ba87dc3d930ba6a6552960b970449ea6d61aedfc65bada156ca04e5af94e38`