v0.1.5

What's new? 🎉🎉

Improvements ✨✨

Polars support for datasets and for all functions. Now you can load the datasets as polars.DataFrame and use the functions with polars.DataFrame.

Bug fixes 🐛🐛

v0.1.4

What's new? 🎉🎉

Improvements ✨✨

Range Cut function, now incorporates an attribute wavenumbers_ that contains the cut wavenumbers

Bug fixes 🐛🐛

v0.1.3

What's new? 🎉🎉

Improvements ✨✨

Updated sklearn API, there is not effect on the functionality

Bug fixes 🐛🐛

v.0.1.2

What's Changed

• Create dependabot.yml by @paucablop in #47
• chore(deps-dev): bump notebook from 6.5.4 to 7.0.6 by @dependabot in #52
• Feature selection by @paucablop in #59

New Contributors

• @dependabot made their first contribution in #52

Full Changelog: v0.1.1...v0.1.2

v0.1.1

What's new? 🎉🎉

Include data augmentation module

Improvements ✨✨

Bug fixes 🐛🐛

v0.1.0

Releasing v0.1.0, it is equivalent to v0.0.28

v0.0.28

What's new? 🎉🎉

add coffee dataset

Improvements ✨✨

Bug fixes 🐛🐛

v0.0.27

What's new? 🎉🎉

• PointScaler: Scale your spectra by the intensity value given at a certain index or wavenumber! This substitutes the old IndexScaler, as it extends its functionality
• SelectFeautes: An advanced feature selector compare to Range Cut. It allows you to choose any range of indices or wavenumbers (continuous or discontinuous) and select the features

Improvements ✨✨

Bug fixes 🐛🐛

v0.0.26

What's new? 🎉🎉

• MinMaxScaler: change functionality, not it will subtract the min and divide by the difference between the min and the max. If the parameter use_min is False, then it will just divide by the max.

Improvements ✨✨

Bug fixes 🐛🐛

v0.0.25

What's new? 🎉🎉

Improvements ✨✨

Bug fixes 🐛🐛

• RangeCut now has a different input order: start, end and wavenumber (optional). Optional inputs are defined at the end. start and end index are found after fitting the method and not upon instantiation. This is because in scikitlearn, instanciation attributes cannot be modified.

• ConstantCorrection: Same changes as RangeCut