A test-driven framework for formally validating scientific models against data.
Project description
SciUnit: A Test-Driven Framework for Formally Validating Scientific Models Against Data
Concept
Documentation
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sciunit-0.2.6.tar.gz
(67.2 kB
view hashes)
Built Distribution
sciunit-0.2.6-py3-none-any.whl
(80.4 kB
view hashes)