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

Project description

Python package RTFD Binder Coveralls Repos using Sciunit Downloads from PyPI

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

Concept

The conference paper

Documentation

Colab
Jupyter Tutorials
API Documentation

Installation

pip install sciunit

or

conda install -c conda-forge sciunit

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


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