LOTUS Regression
A multi-linear regression model specifically designed for use in calculation of trends for atmospheric constituents. Developed as part of the LOTUS initiative (https://www.sparc-climate.org/activities/ozone-trends/, https://lotus.aeronomie.be)
Installation Requirements
The code is tested on Python versions 3.8, 3.9, 3,10, 3.11 and should work on any of them,
however we recommend using the Anaconda python distribution.
Documentation
For more indepth documentation see http://arg.usask.ca/docs/LOTUS_regression/
2 maintainers
Release files for LOTUS-regression 0.8.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lotus_regression-0.8.3.tar.gz | 9.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| LOTUS_regression-0.8.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.0 MB
Release files / lotus_regression-0.8.3.tar.gz
| Download URL | lotus_regression-0.8.3.tar.gz |
|---|---|
| Size | 9.7 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Yes |
| Uploaded via |
twine/4.0.1 CPython/3.11.9
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Release files / LOTUS_regression-0.8.3-py3-none-any.whl
| Download URL | LOTUS_regression-0.8.3-py3-none-any.whl |
|---|---|
| Size | 294.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/4.0.1 CPython/3.11.9
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