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.
Release files for sciunit 0.2.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sciunit-0.2.8.tar.gz | 254.7 kB | Details |
Release files / sciunit-0.2.8.tar.gz
| Download URL | sciunit-0.2.8.tar.gz |
|---|---|
| Size | 254.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.10.8
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