access-experiment-generator
About
The main role of the ACCESS experiment generator is to streamline the creation of one or more experiment configurations from a "control" experiment setup. It reduces manual editing and ensures consistent, repeatable workflows for large ensembles.
Key features
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Parameter perturbation / Configuration changes
- Users provide a set or suite of parameter changes in a YAML input file.
- The generator applies these changes to relevant configurations.
- It can generate multiple experiments automatically, making it especially useful for large perturbation ensembles.
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Branch-based storage approach
- The generator checks out a control branch in a git repository.
- For each perturbation, it creates a new branch containing modified parameters.
- Changes are then committed on that branch and can be pushed back to the github repository.
1 maintainer
Metadata
1 maintainer
Release files for experiment-generator 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| experiment_generator-1.0.0.tar.gz | 32.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| experiment_generator-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 56.8 kB
Release files / experiment_generator-1.0.0.tar.gz
| Download URL | experiment_generator-1.0.0.tar.gz |
|---|---|
| Size | 32.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / experiment_generator-1.0.0-py3-none-any.whl
| Download URL | experiment_generator-1.0.0-py3-none-any.whl |
|---|---|
| Size | 24.2 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
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PyPI Publish Attestation
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