oceanVal is a Python package designed to automate the process of validating ocean models against observational datasets. It provides a suite of tools to facilitate the comparison of model outputs with various observational data sources, enabling researchers to assess model performance effectively.
Core abilities of oceanVal include:
Matching model output variables to observational datasets
Assesing spatial and temporal performance of ocean models
Assessing model skill using a variety of statistical metrics
Asssessing extent of model biases
Generating comprehensive validation reports in html format
Metadata
Release files for oceanval 0.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| oceanval-0.4.0.tar.gz | 8.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| oceanval-0.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.2 MB
Release files / oceanval-0.4.0.tar.gz
| Download URL | oceanval-0.4.0.tar.gz |
|---|---|
| Size | 8.4 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
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Release files / oceanval-0.4.0-py3-none-any.whl
| Download URL | oceanval-0.4.0-py3-none-any.whl |
|---|---|
| Size | 3.8 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|